Systems and methods for displaying a movement of a vehicle on a map

ABSTRACT

A method for displaying a smooth movement of a vehicle on a map may include obtaining a route, a last real-time location of the vehicle, and a last uploading time point. The method may also include obtaining driving data of one or more neighboring vehicles and determining a predicted location of the vehicle at a prediction generating time point. The method may further include displaying a smooth movement of the vehicle from the last real-time location to the predicted location on a map. A method for displaying a driving path of a vehicle on a map may include obtaining a request for displaying a driving path of a vehicle, location information of the vehicle, and scene related information associated with the driving path. The method may further include verifying the location information based on the scene related information and displaying the driving path of the vehicle on a map.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. patent applicationSer. No. 16/221,505, filed on Dec. 15, 2018, now U.S. Pat. No.10,777,080, which is a continuation of International Application No.PCT/CN2018/091824, filed on Jun. 19, 2018, which claims priority toChinese Patent Application No. 201710471851.8, filed on Jun. 20, 2017and Chinese Patent Application No. 201710466200.X, filed on Jun. 19,2017. The entire contents of all applications are incorporated herein byreference.

TECHNICAL FIELD

The present disclosure generally relates to communication technology,and in particular, to systems and methods for displaying a movement of avehicle on a digital map.

BACKGROUND

Public transportation services and online car-hailing services havebecome major travel means for people. If people have an access toreal-time information of a vehicle, such as a bus, they may not have tospend a long time waiting at a bus station. In some embodiments, thevehicle may upload real-time information, including a location of thevehicle, at a predetermined time interval. A user (e.g., a passenger)may query the location of a vehicle through a terminal device (e.g., amobile phone). However, the real-time information of a vehicle is oftenlimited due to various objective conditions. For example, the user mayonly query a real-time location uploaded by a bus 5 minute ago, but maynot know the current location of the bus or a current driving status ofthe bus.

Additionally, for the monitoring and management of a vehicle, a drivingstatus of the vehicle may be evaluated based on driving data of thevehicle. For example, the driving data may include images, sounds,and/or the speed of the vehicle recorded during the driving process.However, such information and an actual driving process of the vehicleare often separated. In particular, a continuous changing process ofgeographical locations of the vehicle is difficult to be shown, thusreducing efficiency of the monitoring and management of the vehicle.Therefore, it is desirable to provide systems and methods for displayinga movement of a vehicle more efficiently on a map.

SUMMARY

According to an aspect of the present disclosure, a method fordisplaying a smooth movement of a vehicle on a map is provided. Themethod may be implemented on a computing device having at least oneprocessor, at least one computer-readable storage medium, and acommunication platform connected to a network. The method may includeobtaining a route of a vehicle via communicating with a service providerover a network. The method may also include obtaining a last real-timelocation of the vehicle on the route and a last uploading time pointcorresponding to the last real-time location. The method may alsoinclude obtaining driving data of one or more neighboring vehiclesassociated with the vehicle via communicating with the service providerover the network. The method may further include determining a predictedlocation of the vehicle on the route at a prediction generating timepoint based on the last real-time location, the last uploading timepoint, and the driving data of one or more neighboring vehiclesassociated with the vehicle. The method may further include displaying asmooth movement of the vehicle from the last real-time location to thepredicted location on a map implemented on a terminal device.

In some embodiments, the driving data of the one or more neighboringvehicles associated with the vehicle may include velocities of the oneor more neighboring vehicles.

In some embodiments, determining the predicted location of the vehicleon the route at the prediction generating time point may includedetermining a velocity of the vehicle based on velocities of the one ormore neighboring vehicles associated with the vehicle, determining apredicted distance that the vehicle travels from the last uploading timepoint to the prediction generating time point based on the velocity, anddetermining the predicted location of the vehicle on the route at theprediction generating time point based on the predicted distance and thelast real-time location.

In some embodiments, the driving data of the one or more neighboringvehicles associated with the vehicle may include durations of the one ormore neighboring vehicles to traverse one or more parts of the route.

In some embodiments, determining the predicted location of the vehicleon the route at the prediction generating time point may includedetermining a predicted distance that the vehicle traverses from thelast uploading time point to the prediction generating time point basedon the durations of the one or more neighboring vehicles to traverse oneor more parts of the route. Determining the predicted location of thevehicle on the route at the prediction generating time point may alsoinclude determining the predicted location of the vehicle on the routeat the prediction generating time point based on the predicted distanceand the last real-time location.

In some embodiments, the method may further include determining adistance between the last real-time location and a station near theroute. The method may further include determining whether the distanceis smaller than a threshold. In response to the determination that thedistance is smaller than the threshold, the method may includedisplaying the vehicle in a stationary status at a predicted locationbetween the last real-time location and the station for a first durationon the map implemented on the terminal device.

In some embodiments, the method may further include obtaining a currentreal-time location of the vehicle. The method may further includedetermining whether the predicted location at the prediction generatingtime point is ahead of the current real-time location of the vehicle. Inresponse to the determination that the predicted location at theprediction generating time point is ahead of the current real-timelocation of the vehicle, the method may further include displaying thevehicle in a stationary status at the predicted location on the mapimplemented on the terminal device until the current real-time locationof the vehicle arrives at the predicted location.

According to another aspect of the present disclosure, a system fordisplaying a smooth movement of a vehicle on a map is provided. Thesystem may include at least one storage medium storing a set ofinstructions, at least one communication platform connected to anetwork, and at least one processor configured to communicate with theat least one storage medium or the at least one communication platform.When executing the set of instructions, the at least one processor maybe directed to cause the system to obtain a route of a vehicle viacommunicating with a service provider over a network, and obtain a lastreal-time location of the vehicle on the route and a last uploading timepoint corresponding to the last real-time location. The at least oneprocessor may be further directed to cause the system to obtain drivingdata of one or more neighboring vehicles associated with the vehicle viacommunicating with the service provider over the network. The at leastone processor may be further directed to cause the system to determine apredicted location of the vehicle on the route at a predictiongenerating time point based on the last real-time location, the lastuploading time point, and the driving data of one or more neighboringvehicles associated with the vehicle. The at least one processor may befurther directed to cause the system to display a smooth movement of thevehicle from the last real-time location to the predicted location on amap implemented on a terminal device.

According to another aspect of the present disclosure, a non-transitorycomputer readable medium for displaying a smooth movement of a vehicleis provided. The non-transitory computer readable medium may include aset of instructions. When executed by at least one processor, the set ofinstructions may direct the at least one processor to effectuate amethod. The method may include obtaining a route of a vehicle viacommunicating with a service provider over a network, and obtaining alast real-time location of the vehicle on the route and a last uploadingtime point corresponding to the last real-time location. The method mayfurther include obtaining driving data of one or more neighboringvehicles associated with the vehicle via communicating with the serviceprovider over the network. The method may further include determining apredicted location of the vehicle on the route at a predictiongenerating time point based on the last real-time location, the lastuploading time point, and the driving data of one or more neighboringvehicles associated with the vehicle. The method may further includedisplaying a smooth movement of the vehicle from the last real-timelocation to the predicted location on a map implemented on a terminaldevice.

According to another aspect of the present disclosure, a method fordisplaying a driving path of a vehicle on a map is provided. The methodmay be implemented on a computing device having at least one processor,at least one computer-readable storage medium, and a communicationplatform connected to a network. The method may include obtaining arequest for displaying a driving path of a vehicle from a terminaldevice and obtaining location information of the vehicle. The method mayfurther include obtaining scene related information associated with thedriving path of the vehicle. The method may further include verifyingthe location information based on the scene related information. Themethod may further include displaying the driving path of the vehiclebased on the verified location information on a map implemented on theterminal device.

In some embodiments, the scene related information associated with thedriving path of the vehicle may include at least one of videoinformation related to scenes along the driving path of the vehicle,image information related to the scenes along the driving path of thevehicle, or audio information related to the scenes along the drivingpath of the vehicle.

In some embodiments, obtaining the scene related information associatedwith the driving path of the vehicle may include communicating with aninformation acquisition device in the vehicle over the network, andobtaining at least one of the video information, the image information,or the audio information recorded by the information acquisition deviceover the network.

In some embodiments, verifying the location information based on thescene related information may include identifying target objects on thedriving path of the vehicle based on the video information, imageinformation, or audio information, and determining whether the locationinformation of the vehicle needs to be corrected based on the targetobjects on the driving path. The method may also include, in response toa determination that the location information of the vehicle associatedwith the driving path needs to be corrected, correcting the locationinformation of the vehicle based on the target objects on the drivingpath of the vehicle.

In some embodiments, the method may further include displaying thedriving path of the vehicle based on the corrected location informationof the vehicle on the map implemented on the terminal device.

In some embodiments, displaying the driving path of the vehicle based onthe verified location information on a map implemented on the terminaldevice may include obtaining an actual driving path generating speed ofthe vehicle, and displaying dynamically the driving path of the vehicleon the map based on the actual driving path generating speed of thevehicle.

In some embodiments, displaying the driving path of the vehicle based onthe verified location information on a map implemented on the terminaldevice may include dividing the driving path of the vehicle into aplurality of segments and determining displaying properties for theplurality of segments. Displaying the driving path of the vehicle basedon the verified location information on a map implemented on theterminal device may further include displaying the driving path of thevehicle on the map based on the displaying properties for the pluralityof segments. At least two neighboring segments may have differentdisplaying properties.

In some embodiments, the displaying properties for the plurality ofsegments may be determined based on at least one of traffic conditionrelated to each of the plurality of segments, time information relatedto each of the plurality of segments, driver information related to eachof the plurality of segments, or driving data related to each of theplurality of segments.

In some embodiments, the displaying properties for the plurality ofsegments include at least one of brightness of the color, hue of thecolor, or thickness of the driving path.

In some embodiments, the method may further include obtaining abnormalevents of the vehicle in a historical period. The method may furtherinclude determining whether an abnormal event occurred on the drivingpath of the vehicle. The method may further include, in response to adetermination that an abnormal event occurred on the driving path of thevehicle, tagging a corresponding location to the abnormal event on thedriving path of the vehicle.

According to another aspect of the present disclosure, a system fordisplaying a driving path of a vehicle on a map is provided. The systemmay include at least one storage medium storing a set of instructions,at least one communication platform connected to a network, and at leastone processor. The at least one processor may be configured tocommunicate with the at least one storage medium or the at least onecommunication platform. When executing the set of instructions, the atleast one processor may be directed to cause the system to obtain arequest for displaying a driving path of a vehicle from a terminaldevice and obtain location information of the vehicle associated withthe driving path via communicating with a service provider over anetwork. The at least one processor may be further directed to cause thesystem to obtain scene related information associated with the drivingpath of the vehicle and verify the location information based on thescene related information. The at least one processor may be furtherdirected to cause the system to display the driving path of the vehiclebased on the verified location information on a map implemented on theterminal device.

According to another aspect of the present disclosure, a non-transitorycomputer readable medium for displaying a driving path of a vehicle on amap is provided. The non-transitory computer readable medium may includea set of instructions. When executed by at least one processor, the setof instructions may direct the at least one processor to effectuate amethod. The method may include obtaining a request for displaying adriving path of a vehicle from a terminal device. The method may alsoinclude obtaining location information of the vehicle associated withthe driving path via communicating with a service provider over anetwork and obtaining scene related information associated with thedriving path of the vehicle. The method may also include verifying thelocation information based on the scene related information. The methodmay also display the driving path of the vehicle based on the verifiedlocation information on a map implemented on the terminal device.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary transportationinformation system according to some embodiments of the presentdisclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/orsoftware components of a computing device according to some embodimentsof the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of a mobile device according to some embodiments ofthe present disclosure;

FIGS. 4A-4C are block diagrams illustrating exemplary data processingdevices according to some embodiments of the present disclosure;

FIG. 5 is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure;

FIGS. 6A and 6B are block diagrams illustrating exemplary dataprocessing devices according to some embodiments of the presentdisclosure;

FIG. 7 is a block diagram illustrating an exemplary display device fordisplaying a vehicle driving path according to some embodiments of thepresent disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for displaying asmooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 9 is a flowchart illustrating an exemplary process for displaying asmooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 10 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 11 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 12 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 13 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure;

FIG. 14 is a flowchart illustrating an exemplary process for displayinga driving path of a vehicle according to some embodiments of the presentdisclosure;

FIG. 15 is a flowchart illustrating an exemplary process for displayinga driving path of a vehicle according to some embodiments of the presentdisclosure;

FIG. 16 is a schematic diagram illustrating exemplary segments dividedbased on a unit time according to some embodiments of the presentdisclosure;

FIG. 17 is a schematic diagram illustrating exemplary segments dividedbased on a unit time according to some embodiments of the presentdisclosure;

FIG. 18 is a schematic diagram illustrating exemplary segments dividedbased on drivers according to some embodiments of the presentdisclosure;

FIG. 19 is a schematic diagram illustrating exemplary segments dividedbased on traffic conditions according to some embodiments of the presentdisclosure;

FIG. 20 is a schematic diagram illustrating exemplary segments andlabelled abnormal events according to some embodiments of the presentdisclosure; and

FIG. 21 is a schematic diagram illustrating an exemplary correction of adriving path of a vehicle according to some embodiments of the presentdisclosure.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled inthe art to make and use the present disclosure and is provided in thecontext of a particular application and its requirements. Variousmodifications to the disclosed embodiments will be readily apparent tothose skilled in the art, and the general principles defined herein maybe applied to other embodiments and applications without departing fromthe spirit and scope of the present disclosure. Thus, the presentdisclosure is not limited to the embodiments shown but is to be accordedthe widest scope consistent with the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

The flowcharts used in the present disclosure illustrate operations thatsystems implement according to some embodiments of the presentdisclosure. It is to be expressly understood, the operations of theflowchart may be implemented not in order. Conversely, the operationsmay be implemented in inverted order, or simultaneously. Moreover, oneor more other operations may be added to the flowcharts. One or moreoperations may be removed from the flowcharts.

Moreover, while the systems and methods disclosed in the presentdisclosure are described primarily regarding assigning service requestsfor transportation services, it should also be understood that this isonly one exemplary embodiment. The systems or methods of the presentdisclosure may be applied to any other kind of online to offlineservices. For example, the system or method of the present disclosuremay be applied to transportation systems of different environmentsincluding land, ocean, aerospace, or the like, or any combinationthereof. The vehicle of the transportation systems may include a taxi, aprivate car, a hitch, a bus, a train, a bullet train, a high-speed rail,a subway, a vessel, an aircraft, a spaceship, a hot-air balloon, adriverless vehicle, or the like, or any combination thereof. Thetransportation system may also include any transportation system formanagement and/or distribution, for example, a system for sending and/orreceiving an express. The application of the system or method of thepresent disclosure may include a webpage, a plug-in of a browser, aterminal device terminal, a custom system, an internal analysis system,an artificial intelligence robot, or the like, or any combinationthereof.

The terms “passenger,” “requester,” “requestor,” “service requester,”“service requestor,” and “customer” in the present disclosure are usedinterchangeably to refer to an individual, an entity or a tool that mayrequest or order a service. Also, the terms “driver,” “provider,”“service provider,” and “supplier” in the present disclosure are usedinterchangeably to refer to an individual, an entity or a tool that mayprovide a service or facilitate the providing of the service. The term“user” in the present disclosure may refer to an individual, an entityor a tool that may request a service, order a service, provide aservice, or facilitate the providing of the service. In the presentdisclosure, terms “requester” and “requester terminal” may be usedinterchangeably, and terms “provider” and “provider terminal” may beused interchangeably.

The terms “request,” “service,” “service request,” and “order” in thepresent disclosure are used interchangeably to refer to a request thatmay be initiated by a passenger, a requester, a service requester, acustomer, a driver, a provider, a service provider, a supplier, or thelike, or any combination thereof. The service request may be accepted byany one of a passenger, a requester, a service requester, a customer, adriver, a provider, a service provider, or a supplier. The servicerequest may be chargeable or free.

It should be noted that an online to offline service, such as onlinetaxi-hailing including taxi hailing combination services, is a new formof service rooted only in post-Internet era. It provides technicalsolutions to users and service providers that could raise only inpost-Internet era. In pre-Internet era, when a passenger hails a taxi onthe street, the taxi request and acceptance occur only between thepassenger and one taxi driver that sees the passenger. If the passengerhails a taxi through a telephone call, the service request andacceptance may occur only between the passenger and one service provider(e.g., one taxi company or agent). Online taxi, however, allows a userof the service to real-time and automatically distribute a servicerequest to a vast number of individual service providers (e.g., taxi)distance away from the user. It also allows a plurality of serviceproviders to respond to the service request simultaneously and inreal-time. Therefore, through the Internet, the online on-demandtransportation systems may provide a much more efficient transactionplatform for the users and the service providers that may never meet ina traditional pre-Internet transportation service system.

In an aspect, the present disclosure is directed to systems and methodsfor displaying a smooth movement of a vehicle on a map implemented on aterminal device. The system may obtain a last real-time location of thevehicle on a predetermined route (e.g., a bus line, or a navigationroute), and driving data of one or more neighboring vehicles associatedwith the vehicle, and predict a location of the vehicle on the route ata regular interval based on the last real-time location and the drivingdata of one or more neighboring vehicles associated with the vehicle.The predicted location of the vehicle may be transmitted to the terminaldevice to display a smooth movement of the vehicle.

In another aspect, the present disclosure is directed to systems andmethods for displaying a driving path of a vehicle on a map implementedon a terminal device. The system may obtain location information andscene related information (e.g., video information, image information,audio information, etc.) associated with the location information. Thesystem may verify the location information using the scene relatedinformation. For instance, the processor may identify one or more targetobjects on the driving path of the vehicle based on the scene relatedinformation, and determine whether the location information of thevehicle associated with the driving path needs to be corrected. Thesystem may transmit the verified location information to the terminaldevice to display the driving path of the vehicle.

FIG. 1 is a schematic diagram illustrating an exemplary transportationinformation system according to some embodiments of the presentdisclosure. For example, the transportation information system 100 maybe used to implement transportation services such as publictransportation services, online car-hailing services, or the like. Thepublic transportation services may include bus services, shuttleservices, train services, plane services, ship services, or the like.The online car-hailing services may include taxi-hailing services,chauffeur services, express car services, carpooling services, driverhiring services, or the like, or any combination thereof. In someembodiments, the transportation information system 100 may include aserver 110, a management information system (MIS) 120, one or moreinformation acquisition devices 130 (e.g., 130-1, 130-2) and a network140.

In some embodiments, the server 110 may be a single server, or a servergroup. The server group may be centralized, or distributed (e.g., theserver 110 may be a distributed system). In some embodiments, the server110 may be local or remote. For example, the server 110 may accessinformation and/or data from the MIS 120 or the information acquisitiondevice 130 via the network 140. As another example, the server 110 maybe directly connected to the MIS 120 to access information and/or data.In some embodiments, the server 110 may be implemented on a cloudplatform. Merely by way of example, the cloud platform may include aprivate cloud, a public cloud, a hybrid cloud, a community cloud, adistributed cloud, an inter-cloud, a multi-cloud, or the like, or anycombination thereof. In some embodiments, the server 110 may beimplemented on a computing device 200 having one or more componentsillustrated in FIG. 2.

In some embodiments, the server 110 may include a processing engine. Theprocessing engine may process information and/or data relating to aservice request to perform one or more functions described in thepresent disclosure. For example, the processing engine may obtainreal-time locations of a vehicle and predict a location for the vehicle.The processing engine may also generate a driving path of a vehiclebased on the real-time locations and the predicted locations. In someembodiments, the processing engine may include one or more processingengines (e.g., single-core processing engine(s) or multi-coreprocessor(s)). The processing engine may include a central processingunit (CPU), an application-specific integrated circuit (ASIC), anapplication-specific instruction-set processor (ASIP), a graphicsprocessing unit (GPU), a physics processing unit (PPU), a digital signalprocessor (DSP), a field programmable gate array (FPGA), a programmablelogic device (PLD), a controller, a microcontroller unit, a reducedinstruction-set computer (RISC), a microprocessor, or the like, or anycombination thereof.

The MIS 120 may be a type of network management system. In someembodiments, the MIS 120 can be used by an administrator. Theadministrator may be a human being capable of performing networkadministrating. In some embodiments, the administrator may be anintelligent robot or a computer-implemented program that is programmedto perform network administration. In some embodiments, the MIS 120 maybe implemented as an administrator terminal device. For example, theadministrator terminal device may include a mobile device, a tabletcomputer, a laptop computer, a built-in device in a vehicle, or thelike, or any combination thereof. In some embodiments, the MIS 120 mayrun a program of an application so as to implement associated functionsof the application. For example, when the MIS 120 runs a program ofdisplaying a driving path of a vehicle, the MIS 120 may be configured asan administrator terminal device for implementing the displayingfunction.

In some embodiments, the MIS 120 may obtain information from the one ormore components of the transportation information system 100 (e.g., theserver 110, and/or the information acquisition device 130). For example,the MIS 120 may obtain a driving path of a vehicle from the server 110and display the driving path on a map. As another example, the MIS 120may obtain image information, video information, audio information,etc., from the information acquisition device 130. In some embodiments,the MIS 120 may display a smooth movement of the vehicle on the map. Insome embodiments, the MIS 120 may also obtain driving data of thevehicle via communicating with a service provider (not shown in FIG. 1)over the network 140. As used herein, a service provider refers to adriver, a terminal device used by a driver, a build-in device of thevehicle associated with the driver, or the like. In some embodiments,the MIS 120 may be configured to monitor and manage one or morevehicles. For example, the driving data of a vehicle may include a speedof the vehicle, a direction that the vehicle is driving to, etc. The MIS120 may obtain abnormal events that occurred on the driving path of thevehicle based on the driving data of the vehicle, such as an abruptbreak, a sharp turn, an overspeed behavior, etc. The MIS 120 may furtherdisplay the abnormal events, for example, in words, or using symbols, onthe driving path. In some embodiments, the MIS 120 may notify theadministrator of the abnormal events. In some embodiments, theadministrator may input an instruction and/or notify the informationrelated to the vehicle to the driver of the vehicle via the MIS 120.

The one or more information acquisition devices 130 (e.g., 130-1, 130-2)may acquire information associated with a vehicle. In some embodiments,the information acquisition device 130 may run a program of anapplication so as to implement associated functions of the application.For example, when running a program related to a driving path of avehicle, the information acquisition device 130 may be configured toacquire a real-time location of the vehicle and scene relatedinformation associated with the driving path of the vehicle. Forinstance, the scene related information may include information orobjects recognized from images, videos, and/or audio segments recordedduring the driving process of the vehicle. In some embodiments, theinformation acquisition device 130 may be a built-in device of thevehicle. In some embodiments, the information acquisition device 130 maybe a terminal device associated with the driver of the vehicle. Forexample, the terminal device associated with the driver of the vehiclemay include a mobile device, a tablet computer, a laptop computer, abuilt-in device in a vehicle, or the like, or any combination thereof.It should be noted that the information acquisition devices 130-1 and130-2 shown in FIG. 1 are merely for illustration.

The network 140 may facilitate exchange of information and/or data. Insome embodiments, one or more components of the transportationinformation system 100 (e.g., the server 110, the MIS 120 and/or theinformation acquisition device 130) may transmit information and/or datato other component(s) of the transportation information system 100 viathe network 140. For example, the server 110 may obtain image data,video data and/or audio data from the information acquisition device 130via the network 140. In some embodiments, the network 140 may be anytype of wired or wireless network, or any combination thereof. Merely byway of example, the network 140 may include a cable network, a wirelinenetwork, an optical fiber network, a telecommunications network, anintranet, an Internet, a local area network (LAN), a wide area network(WAN), a wireless local area network (WLAN), a metropolitan area network(MAN), a public telephone switched network (PSTN), a Bluetooth network,a ZigBee network, a near field communication (NFC) network, or the like,or any combination thereof. In some embodiments, the network 140 mayinclude one or more network access points. For example, the network 140may include wired or wireless network access points such as basestations and/or internet exchange points, through which one or morecomponents of the transportation information system 100 may be connectedto the network 140 to exchange data and/or information.

In some embodiments, the transportation information system 100 mayfurther include a storage device. The storage device may storeinformation relating and/or instructions. In some embodiments, thestorage device may store data obtained from one or more components ofthe transportation information system 100 (e.g., the server 110, the MIS120 and/or the information acquisition device 130). In some embodiments,the storage device may store data and/or instructions that the server110 may execute or use to perform exemplary methods described in thepresent disclosure. For example, the storage device may store dataand/or instructions for displaying a driving path of a vehicle. In someembodiments, the storage device may store location information relatedto the vehicle. In some embodiments, the storage device may include amass storage, a removable storage, a volatile read-and-write memory, aread-only memory (ROM), or the like, or any combination thereof.Exemplary mass storage may include a magnetic disk, an optical disk, asolid-state drive, etc. Exemplary removable storage may include a flashdrive, a floppy disk, an optical disk, a memory card, a zip disk, amagnetic tape, etc. Exemplary volatile read-and-write memory may includea random access memory (RAM). Exemplary RAM may include a dynamic RAM(DRAM), a double date rate synchronous dynamic RAM (DDR SDRAM), a staticRAM (SRAM), a thyristor RAM (T-RAM), and a zero-capacitor RAM (Z-RAM),etc. Exemplary ROM may include a mask ROM (MROM), a programmable ROM(PROM), an erasable programmable ROM (EPROM), an electrically erasableprogrammable ROM (EEPROM), a compact disk ROM (CD-ROM), and a digitalversatile disk ROM, etc. In some embodiments, the storage device may beimplemented on a cloud platform. Merely by way of example, the cloudplatform may include a private cloud, a public cloud, a hybrid cloud, acommunity cloud, a distributed cloud, an inter-cloud, a multi-cloud, orthe like, or any combination thereof.

In some embodiments, the storage device may be connected to the network140 to communicate with one or more components of the transportationinformation system 100. In some embodiments, the storage device may bedirectly connected to or communicate with one or more components of thetransportation information system 100. In some embodiments, the storagedevice may be part of the server 110 and/or the MIS 120.

One of ordinary skill in the art would understand that when an elementof the transportation information system 100 performs, the element mayperform through electrical signals and/or electromagnetic signals. Forexample, when the server 110 processes a task, such as obtaining areal-time location of the vehicle from the information acquisitiondevice 130 via the network 140, the server 110 may operate logiccircuits in its processor to process such task. The server 110 maycommunicate with the transportation information system 100 via a wirednetwork, the at least one information exchange port may be physicallyconnected to a cable, which may further transmit the electrical signalsto an input port (e.g., an information exchange port) of the requesterterminal 130. If the server 110 communicates with the transportationinformation system 100 via a wireless network, the at least oneinformation exchange port may be one or more antennas, which may convertthe electrical signals to electromagnetic signals. Within an electronicdevice, such as the MIS 120, and/or the server 110, when a processorthereof processes an instruction, sends out an instruction, and/orperforms an action, the instruction and/or action is conducted viaelectrical signals. For example, when the processor retrieves or savesdata from a storage medium (e.g., the storage device), the processor maysend out electrical signals to a read/write device of the storagemedium, which may read or write structured data in the storage medium.The structured data may be transmitted to the processor in the form ofelectrical signals via a bus of the electronic device. Here, anelectrical signal may be one electrical signal, a series of electricalsignals, and/or a plurality of discrete electrical signals.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an electronic device according to someembodiments of the present disclosure. In some embodiments, the server110, the MIS 120, and/or the information acquisition device 130 may beimplemented on the electronic device 200 shown in FIG. 2. The particularsystem may use a functional block diagram to explain the hardwareplatform containing one or more user interfaces. In some embodiments,the electronic device 200 may be a computing device with general orspecific functions. Both types of the computing devices may beconfigured to implement any particular system according to someembodiments of the present disclosure. The electronic device 200 may beconfigured to implement any components that perform one or morefunctions disclosed in the present disclosure. For example, theelectronic device 200 may implement any component of the transportationinformation system 100 as described herein. In FIGS. 1-2, only one suchelectronic device is shown purely for convenience purposes. One ofordinary skill in the art would understood that the functions relatingto the method of displaying a driving path of a vehicle as describedherein may be implemented in a distributed fashion on a number ofsimilar platforms, to distribute the processing load.

As shown in FIG. 2, the electronic device 200 shown in FIG. 2 mayinclude a processor 210, an internal bus 220, a network port 230, amemory 240, and a nonvolatile storage 250. In some embodiments, othersuitable hardware needed for other functions may also be included in theelectronic device 200. The processor 210 may read computer program fromthe nonvolatile storage 250, and run the program in the memory 240 so asto implement the functions of a display device for displaying a drivingpath of a vehicle. Of course, apart from software implementation, thepresent application does not exclude other implementations, such aslogic devices or a combination of hardware and software. In other words,an execution subject of the processes below may not be limited to logicunits, but may also be hardware or a logic device according to someembodiments of the present disclosure.

The processor 220 may exist in the form of one or more processors (e.g.,logic circuits) for executing program instructions. For example, theprocessor 210 may include interface circuits and processing circuitstherein. The interface circuits may be configured to receive electronicsignals from an internal bus 220, wherein the electronic signals encodestructured data and/or instructions for the processing circuits toprocess. The processing circuits may conduct logic calculations, andthen determine a conclusion, a result, and/or an instruction encoded aselectronic signals. Then the interface circuits may send out theelectronic signals from the processing circuits via the internal bus220.

The nonvolatile storage 250 may include a read only memory (ROM) and/ora random access memory (RAM), for various data files to be processedand/or transmitted by the electronic device 200. The electronic device200 may also include program instructions stored in the ROM, the RAM,and/or other type of non-transitory storage medium to be executed by theprocessor 210. The methods and/or processes of the present disclosuremay be implemented as the program instructions. In some embodiments, theelectronic device 200 may also include an I/O component, supportinginput/output between the electronic device 200 and other components/auser. The electronic device 200 may also receive programming and datavia network communications.

Merely for illustration, only one processor is illustrated in FIG. 2.Multiple processors 210 are also contemplated, and thus operationsand/or method steps performed by one processor 210 as described in thepresent disclosure may also be jointly or separately performed by themultiple processors. For example, if in the present disclosure, theprocessor 210 of the electronic device 200 executes both step A and stepB, it should be understood that step A and step B may also be performedby two different processors 220 jointly or separately in the electronicdevice 200 (e.g., a first processor executes step A and a secondprocessor executes step B, or the first and second processors jointlyexecute steps A and B).

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of a mobile device according to some embodiments ofthe present disclosure. In some embodiments, the MIS 120, theinformation acquisition device 130, and/or a terminal device associatedwith a user may be implemented on the mobile device 300 shown in FIG. 3.For instance, the user may include a service requester (e.g., apassenger), or a service provider (e.g., a driver). As illustrated inFIG. 3, the mobile device 300 may include a communication platform 310,a display 320, a graphic processing unit (GPU) 330, a central processingunit (CPU) 340, an I/O 350, a memory 360, a mobile operating system (OS)370, and a storage 390. In some embodiments, any other suitablecomponent, including but not limited to a system bus or a controller(not shown), may also be included in the mobile device 300.

In some embodiments, the mobile operating system 370 (e.g., iOS™,Android™, Windows Phone™, etc.) and one or more applications 380 may beloaded into the memory 360 from the storage 390 in order to be executedby the CPU 340. The applications 380 may include a browser or any othersuitable mobile apps for receiving and rendering information relating toa vehicle or other information from the transportation informationsystem 100. User interactions with the information stream may beachieved via the I/O 350 and provided to the processing engine 112and/or other components of the transportation information system 100 viathe network 140.

FIG. 4A is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 400 shown in FIG. 4A may include an acquisition module410, a data processing module 420, and a display processing module 430.In some embodiments, the data processing module 400 shown in FIG. 4A maybe an independent device or integrated into the server 110, the MIS 120,the mobile device 300, etc. For example, the data processing device 400may be part of the processor 210.

The acquisition module 410 may obtain information from one morecomponents of the transportation information system 100. In someembodiments, the acquisition module 410 may obtain a route of a vehiclevia communicating with a service provider over a network (e.g., thenetwork 140). In some embodiments, the acquisition module 410 may obtaina last real-time location uploaded by a vehicle and a last uploadingtime point corresponding to the last real-time location. In someembodiments, the acquisition module 410 may obtain driving data of oneor more neighboring vehicles associated with the vehicle viacommunicating with the service provider over the network. For example,the driving data of the one or more neighboring vehicles may includevelocities, moving directions, and/or turning angles of the one or moreneighboring vehicles currently within the predetermined distance fromthe vehicle. As another example, the driving data of the one or moreneighboring vehicles may include the durations of the one or moreneighboring vehicles to traverse one or more parts of the route.

The data processing module 420 may process data related to the vehicle.In some embodiments, the data processing module 420 may determine apredicted location of the vehicle on the route at a predictiongenerating time point based on the last real-time location, the lastuploading time point, and the driving data of one or more neighboringvehicles associated with the vehicle. In some embodiments, the dataprocessing module 420 may determine a predicted location for eachpredetermined time period. The predetermined time period may be, forexample, 3 seconds, 5 seconds, 10 seconds, etc.

The display processing module 430 may process data related to the smoothmovement of the vehicle. In some embodiments, the display processingmodule 430 may include a searching unit and a dynamic display unit. Thesearching unit may match the real-time locations and the predictedlocations with the route of the vehicle. For example, the searching unitmay determine track points which are closest to the real-time locationsand the predicted locations for the vehicle from all the track points onthe route. The dynamic display unit may display all the determined trackpoints on a map in a time sequence.

The modules/units in FIG. 4A may be connected to or communicate witheach other via a wired connection or a wireless connection. The wiredconnection may include a metal cable, an optical cable, a hybrid cable,or the like, or a combination thereof. The wireless connection mayinclude a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 4B is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 400 shown in FIG. 4B may include an acquisition module410, a data processing module 420, and a display processing module 430.In some embodiments, the data processing device 400 shown in FIG. 4B maybe an independent device or integrated into the server 110, the MIS 120,the mobile device 300, etc. For example, the data processing device 400may be part of the processor 210. In connection with the description inFIG. 4A, the data processing module 420 may further include a firstanalysis unit 440, a first determination unit 450, and a firstprocessing unit 460.

The first analysis unit 440 may determine a velocity of the vehicle. Insome embodiments, the first analysis unit 440 may determine the velocityof the vehicle based on velocities of one or more neighboring vehiclesthat are currently within a predetermined distance from the vehicle. Insome embodiments, the first analysis unit 440 may determine the durationof the vehicle to traverse one or more parts of the route based ondurations of one or more neighboring vehicles to traverse one or moreparts of the route. In some embodiments, the first analysis unit 440 maydetermine the velocity of the vehicle based on the durations of the oneor more neighboring vehicles to traverse one or more parts of the route.Merely by ways of example, the neighboring vehicles may have traversedthe one or more parts of the route a day ago, a week ago, a month ago,etc.

The first determination unit 450 may determine a predicted distance forthe vehicle. In some embodiments, the first determination unit 450 maydetermine the predicted distance for the vehicle within a time intervalbetween the last uploading time point and the prediction generating timepoint based on the velocity of the vehicle or the duration of thevehicle to traverse one or more parts of the route of the vehicle. Thelast uploading time point may be a time point when the vehicle uploadsthe last real-time location. The prediction generating time point may bean end of a predetermined time period. In some embodiments, the end of acurrent predetermined time period may be the start of a nextpredetermined time period.

The first processing unit 460 may determine a predicted location for thevehicle at the prediction generating time point. In some embodiments,the first processing unit 460 may determine the predicted location forthe vehicle at the prediction generating time point based on apredetermined time period, the last real-time location, the lastuploading time point, driving data of one or more neighboring vehicles,and a route of the vehicle.

The modules/units in FIG. 4B may be connected to or communicate witheach other via a wired connection or a wireless connection. The wiredconnection may include a metal cable, an optical cable, a hybrid cable,or the like, or a combination thereof. The wireless connection mayinclude a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 4C is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 400 shown in FIG. 4C may include an acquisition module410, a data processing module 420, and a display processing module 430.In some embodiments, the data processing device 400 shown in FIG. 4C maybe an independent device or integrated into the server 110, the MIS 120,the mobile device 300, etc. For example, the data processing device 400may be part of the processor 210. In connection with the description inFIG. 4A, the data processing module 420 may further include a firstanalysis unit 440, a first determination unit 450, and a firstprocessing unit 460.

The second analysis unit 470 may determine a velocity of the vehicle.Details regarding the second analysis unit 470 may be found elsewhere(e.g., in connection with the description of the first analysis unit 440in FIG. 4B).

The second determination unit 480 may determine a predicted distance ofthe vehicle. In some embodiments, the second determination unit 480 maydetermine the predicted distance of the vehicle within the predeterminedtime period based on the velocity of the vehicle and a time length ofthe predetermined time period. In some embodiments, the processor 210may determine the predicted distance of the vehicle based on a motion ofthe vehicle at a constant velocity. Thus the predicted distance may beequal to a product of the velocity of the vehicle and a time length ofthe predetermined time period.

The second processing unit 490 may determine a predicted location of thevehicle. In some embodiments, the second processing unit 490 maydetermine the predicted location for the vehicle at an end of eachpredetermined time period based on a last predicted location in a lastpredetermined time period, the predicted distance of the vehicle withinthe each predetermined time period, and a route of the vehicle.

The modules/units in FIG. 4C may be connected to or communicate witheach other via a wired connection or a wireless connection. The wiredconnection may include a metal cable, an optical cable, a hybrid cable,or the like, or a combination thereof. The wireless connection mayinclude a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 5 is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 500 shown in FIG. 5 may include an acquisition module410, a data processing module 420, and a display processing module 430,and a detection module 510. In some embodiments, the data processingdevice 500 shown in FIG. 5 may be an independent device or integratedinto the server 110, the MIS 120, the mobile device 300, etc. Forexample, the data processing device 500 may be part of the processor210. Details regarding the acquisition module 410, the data processingmodule 420, and the display processing module 430 may be found elsewhere(e.g., in connection with FIGS. 4A-4C).

The detection module 510 may determine whether the vehicle isstationary. In some embodiments, the vehicle may stop near a station ordue to congestion/a red traffic light. For example, the detection module510 may determine that the vehicle stops near a station if a distancebetween the last real-time location and a station near the route is lessthan a threshold. As another example, if the velocities of the one ormore neighboring vehicles currently within a predetermined distance fromthe vehicle are zero, the detection module 510 may determine that thevehicle is currently stationary due to congestion/a red traffic light.

If the vehicle is in a stationary status, the data processing module 420may not need to determine a predicted location for the vehicle. If thevehicle is near a station, the displaying processing module 430 may addthe last real-time location to the route and display the vehicle in astationary status at an estimated location between the last real-timelocation and the station or the last real-time location on the route fora first duration on the map implemented on the terminal device. If thevehicle stops due to congestion/a red traffic light, the displayingprocessing module 430 may add the last real-time location to the routeand display the vehicle in a stationary status at the last predictedlocation or the last real-time location on the route for a firstduration on the map implemented on the terminal device.

The modules/units in FIG. 5 may be connected to or communicate with eachother via a wired connection or a wireless connection. The wiredconnection may include a metal cable, an optical cable, a hybrid cable,or the like, or a combination thereof. The wireless connection mayinclude a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 6A is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 600 shown in FIG. 6A may include an elimination module620, an acquisition module 410, a data processing module 420, and adisplay processing module 430. In some embodiments, the data processingdevice 600 shown in FIG. 6A may be an independent device or integratedinto the server 110, the MIS 120, the mobile device 300, etc. Forexample, the data processing device 600 may be part of the processor210. Details regarding the acquisition module 410, the data processingmodule 420, and the display processing module 430 may be found elsewhere(e.g., in connection with FIGS. 4A-4C).

The elimination module 620 may discard an inaccurate real-time locationor an inaccurate predicted location of the vehicle. In some embodiments,if a current real-time location of the vehicle is behind a lastreal-time location on the route along a driving direction of thevehicle, the elimination module 620 may discard the current real-timelocation. In some embodiments, if a currently predicted location isbehind a last predicted location on a route along a driving direction ofthe vehicle, the elimination module 620 may discard the currentlypredicted location. In some embodiments, a vehicle on a given route maytravel one-way along the given route, and thus the elimination module620 may correct inaccurate real-time locations or inaccurate predictedlocations based on the route.

FIG. 6B is a block diagram illustrating an exemplary data processingdevice according to some embodiments of the present disclosure. The dataprocessing device 650 shown in FIG. 6B may include a freezing module630, a receiving module 640, an acquisition module 410, a dataprocessing module 420, and a display processing module 430. In someembodiments, the data processing device 650 shown in FIG. 6B may be anindependent device or integrated into the server 110, the MIS 120, themobile device 300, etc. For example, the data processing device 650 maybe part of the processor 210. Details regarding the acquisition module410, the data processing module 420, and the display processing module430 may be found elsewhere (e.g., in connection with FIGS. 4A-4C).

The receiving module 640 may receive data related to the vehicle. Forexample, the receiving module 640 may receive a current real-timelocation of the vehicle.

The freezing module 630 may freeze a currently displayed location of thevehicle. In some embodiments, if a currently displayed location is aheadof the current real-time location, the freezing module 630 may freezethe currently displayed location of the vehicle. The currently displayedlocation may refer to a location of the vehicle that is currentlydisplayed on a map implemented on the terminal device. In someembodiments, the currently displayed location may be a predictedlocation.

If the currently displayed location is frozen, the display processingmodule 430 may display the vehicle in a stationary status until thecurrent real-time location of the vehicle arrives at the predictedlocation.

The modules/units in FIGS. 6A and 6B may be connected to or communicatewith each other via a wired connection or a wireless connection. Thewired connection may include a metal cable, an optical cable, a hybridcable, or the like, or a combination thereof. The wireless connectionmay include a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 7 is a block diagram illustrating an exemplary display device fordisplaying a driving path of a vehicle according to some embodiments ofthe present disclosure. In some embodiments, the display device 700 fordisplaying a driving path of the vehicle may include a detection unit710, a first acquisition unit 720, a display unit 730, a secondacquisition unit 740, a third acquisition unit 750, a fourth acquisitionunit 760, an identification unit 770, and a correction unit 780. In someembodiments, the display device 700 for displaying a driving path shownin FIG. 7 may be an independent device or integrated into the server110, the MIS 120, the mobile device 300, etc. For example, the displaydevice 700 for displaying a driving path may be part of the processor210.

The detection unit 710 may obtain a query operation. In someembodiments, the query operation may be a request for displaying adriving path of a vehicle within a historical time period or inreal-time.

The first acquisition unit 720 may acquire location information of avehicle within the historical time period or in real-time.

The display unit 730 may display the driving path of the vehicle on amap. In some embodiments, the display unit 730 may the driving path ofthe vehicle on a map based on the obtained location information. Forexample, the display unit 730 may display a generating process of thedriving path according to an actual driving path generating speed of thevehicle or a displaying ratio with respect to the actual driving pathgenerating speed. In some embodiments, the display unit 730 may dividethe driving path into a plurality of segments based on trafficconditions, time information, driver information, driving data, or thelike, or any combination thereof. The segments may be displayed withdifferent displaying properties, such as brightness of the color, hue ofthe color, and/or thickness of the driving path. In some embodiments,the display unit 730 may display an image or play a video/audio when thedriving path of the vehicle is displayed on the map.

The second acquisition unit 740 may obtain abnormal events of thevehicle. In some embodiments, the processor 210 may determine whetherabnormal events occurred in the process for driving the vehicle based onspeed information acquired by the information acquisition device 130.For example, the abnormal events may include an abrupt brake, a suddenacceleration, a sharp turn, and an overspeed behavior, or the like, orany combination thereof. In some embodiments, the second acquisitionunit 740 may add certain labels to locations on the driving path wherethe abnormal events occur so as to mark the abnormal events.

The third acquisition unit 750 may obtain scene related informationassociated with the driving path of the vehicle. In some embodiments,the scene related information may include image information, videoinformation, and/or audio information related to scenes along thedriving path of the vehicle.

The fourth acquisition unit 760 may obtain the scene related informationwithin a historical time period or in real-time. For example, the fourthacquisition unit 760 may obtain image information, video information,and/or audio information within a historical time period or videoinformation/audio information starting from a time point.

The identification unit 770 may identify a target object. In someembodiments, the identification unit 770 may identify a target objectbased on the scene related information related to scenes along thedriving path of the vehicle. The target object may include a building, asquare, etc.

The correction unit 780 may verify the location information based on thescene related information. In some embodiments, the correction unit 780may determining whether the location information of the vehicle needs tobe corrected based on the target objects on the driving path. Merely byways of example, if a location indicated by the location information ofthe vehicle corresponding to a time point is different from a locationof the target object identified from the scene related informationacquired at the same time, the correction unit 780 may determine thatthe location information of the vehicle corresponding to the time pointneed to be corrected. The correction unit 780 may correct the inaccuratelocation information of the vehicle based on the location of the targetobject.

The modules/units in FIG. 7 may be connected to or communicate with eachother via a wired connection or a wireless connection. The wiredconnection may include a metal cable, an optical cable, a hybrid cable,or the like, or a combination thereof. The wireless connection mayinclude a Local Area Network (LAN), a Wide Area Network (WAN), aBluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or acombination thereof. Two or more of the modules may be combined into asingle module, and any one of the modules may be divided into two ormore units.

FIG. 8 is a flowchart illustrating an exemplary process for displaying asmooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 800 shown in FIG. 8may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 800may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 800 may be implemented on a terminaldevice. The operations of the illustrated process 800 presented beloware intended to be illustrative. In some embodiments, the process 800may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 800 asillustrated in FIG. 8 and described below is not intended to belimiting. As shown in FIG. 8, the process 800 may include the followingoperations.

In 802, the processor 210 may obtain a last real-time location uploadedby a vehicle and a last uploading time point corresponding to the lastreal-time location.

In some embodiments, a real-time location may include geographicallocation coordinates. In some embodiments, the vehicle may uploadreal-time locations to the server 110 at a predetermined time interval.For example, the vehicle may upload real-time locations every 30seconds, 45 seconds, 60 seconds, etc. The last real-time location may bea location most recently uploaded by the vehicle.

A vehicle may be equipped with a positioning system. In someembodiments, a terminal device (e.g., the mobile device 300) of a driverof the vehicle may also have a positioning system. A current location ofthe vehicle can be obtained in real-time through the positioning systemof the vehicle or the terminal device of the driver. Thus, the processor210 may obtain a real-time location of the vehicle when the vehicle isin an area under the coverage of a network, such as a general packetradio service (GPRS) network or a code division multiple access (CDMA)network. In some embodiments, a device implementing the positioningtechnology can use a global positioning system (GPS), a globalnavigation satellite system (GLONASS), a compass navigation system(COMPASS), a BeiDou navigation satellite system, a Galileo positioningsystem, a quasi-zenith satellite system (QZSS), etc. In someembodiments, the positioning system may determine a position of thevehicle with a high accuracy based on a differential positioningalgorithm. Merely for illustration purposes, the vehicle may be a bus.

In 804, the processor 210 may determine a predicted location for thevehicle at an end of a predetermined time period based on thepredetermined time period, the last real-time location, the lastuploading time point, driving data of one or more neighboring vehicles,and a route of the vehicle.

As used herein, the neighboring vehicles refer to other vehiclescurrently within a predetermined distance from the vehicle or othervehicles that previously traversed one or more parts of the route. Forexample, the predetermined distance may be 5 meters, 10 meters, 15meters, etc. In some embodiments, the neighboring vehicles may havetraversed the one or more parts of the route a day ago, a week ago, amonth ago, etc. In some embodiments, the driving data of the one or moreneighboring vehicles may include velocities, moving directions, and/orturning angles of the one or more neighboring vehicles currently withinthe predetermined distance from the vehicle. In some embodiments, thedriving data of the one or more neighboring vehicles may include thedurations of the one or more neighboring vehicles to traverse one ormore parts of the route.

In some embodiments, the processor 210 may obtain data associated withall routes of different buses on a map in advance, such as coordinatesof track points and/or station information of each route, or the like. Astorage device (e.g., the nonvolatile storage device 250) may store suchdata as static data. Merely as an example, the route here may be a busline.

In 806, a terminal device (e.g., a mobile device of a user, a displayscreen at a bus station) may display a smooth movement of the vehiclealong the route on a map based on the last real-time location, thepredicted location of the vehicle and the predetermined time period.

In some embodiments, a smooth movement of the vehicle may be generatedby an independent client side device, a backend server, or the like. Itshould be noted that an order that the above operations are performedmay vary. In some embodiments, the processor 210 may determine apredicted location of the vehicle at a prediction generating time pointafter the processor 210 obtains the last real-time location uploaded bythe vehicle. In some embodiments, a predetermined time period may startfrom the last uploading time point, and end at the prediction generatingtime point. In some embodiments, the end of a last predetermined timeperiod may be the start of a current predetermined time period. Forexample, the processor 210 may determine a predicted location for thevehicle at the end of a predetermined time period (e.g., 3 seconds).After the processor 210 obtains a next real-time location uploaded bythe vehicle, the processor 210 may match one or more predicted locationsand the next real-time location with the route of the vehicle, anddisplay the one or more predicted locations and the next real-timelocation on the route, so as to display a smooth movement of thevehicle. Alternatively, as soon as the processor 210 determines eachpredicted location, the processor 210 may match the predicted locationwith the route of the vehicle, and display the each predicted locationon the route. For instance, the terminal device may display a smoothmovement of the vehicle from the last real-time location to thepredicted location on a map implemented on the terminal device. Theorder that the above operations are performed is not limited in thepresent disclosure.

In some embodiments, in order to display a smooth movement of thevehicle in rea-time based on the real-time locations uploaded by thevehicle, the device installed on the vehicle may need to support highspeed data acquisition, data processing, and data uploading. A timeperiod for the vehicle to upload the location information may be set tobe short, e.g., 3 to 5 seconds. A terminal device may display a smoothmovement of the vehicle based on real-time locations of the vehicleuploaded in the time period and a route of the vehicle preset by, forexample, the positioning system or the terminal device. However, 3 to 5seconds may be too short, and the device installed on the vehicle maynot support accurate positioning and uploading locations of the vehiclein such a short time period. For example, a vehicle may determine andupload a real-time location in 30 seconds. In this case, the smoothmovement of the vehicle based on the real-time locations uploaded by thevehicle may not be achieved. If the terminal device displays thereal-time locations uploaded by the vehicle on a route, there may be alot of pauses during the movement of the vehicle. As a result, themovement of the vehicle on the map may demonstrate a sudden shift fromone location to another location. Thus, a user (e.g., a passenger) maynot know whether the vehicle arrives at a certain station in such ashort time.

Thus, the processor 210 may determine a predicted location at the end ofa predetermined time period (e.g., 3 seconds, 5 seconds) before thevehicle uploads a next real-time location based on a last real-timelocation uploaded by the vehicle at a last uploading time point. Theterminal device may display a smooth movement of the vehicle along theroute on a map based on the predicted locations and the last real-timelocation of the vehicle. In some embodiments, when the frequency atwhich the real-time locations are uploaded by the vehicle does not meeta preset frequency, operations in 802 through 806 may be triggered.

In some embodiments, the terminal device for displaying the smoothmovement of the vehicle may be associated with a driver of the vehicle,a passenger on the vehicle, a passenger waiting for the vehicle, anadministrator, etc. In some embodiments, the terminal device associatedwith an administrator may be the MIS 120. In some embodiments, theprocessor 210 and/or the terminal device may obtain a route of thevehicle by communicating with a service provider over a network (e.g.,the network 140). The route of the vehicle may include a predeterminedroute, such as a bus line, a navigation route, or the like. The routemay also be a navigation route.

In some embodiments, when the vehicle uploads a real-time location, thevehicle may also upload identification information related to the routeof the vehicle. The identification information may be used to identifythe route of the vehicle, for example, Bus Line 102, Bus Line 84, or thelike. Taking a bus on Bus Line 84 as an example, there may be multipleways for the bus to upload the identification information. For example,the bus may upload the vehicle identification information (e.g., avehicle license number Jing P TT069) and the bus line (Bus Line 84)together. As another example, the bus may only upload the vehicleidentification information (e.g., Jing P TT069). An electronic device,such as the server 110 and the electronic device 200, may determine aroute of the bus based on a schedule of other buses running on the samebus line. For example, if the schedule shows that the bus “Jing P TT069”is on Bus Line 102, the terminal device may display a real-time smoothmovement of the vehicle based on a route corresponding to the Bus Line102.

In some embodiments, the predetermined time period may be determinedaccording to actual needs. For example, the processor 210 may determinethe predetermined time period based on factors such as data processingability, processing efficiency, and the display of the smooth movement.Thus, the processor 210 may determine the number of predicted locationsfor the vehicle. Merely for illustration purposes, the predeterminedtime period may be 5 seconds. If a bus on Bus Line 102 uploads a lastreal-time location at 3:00:00, the last uploading time point may be3:00:00, the terminal device may display the vehicle identificationinformation at the last real-time location on the route of Bus Line 102.The vehicle identification information herein may be used to mark thelocation of the vehicle on a map. For example, the vehicleidentification information may be presented in forms of an icon with ashape of a vehicle so as to visually show the current location of thevehicle. If the vehicle does not upload a next real-time location or theuploaded real-time location does not change after 5 seconds, theprocessor 210 may determine a predicted location for the vehicle. Insome embodiments, the processor 210 may determine a predicted locationfor the vehicle at 3:00:05 based on the last real-time location uploadedby the vehicle and a driving status of one or more neighboring vehicles.Similarly, the processor 210 may determine predicted locations for thevehicle at 3:00:10, 3:00:15, and 3:00:20, respectively. The processor210 may match the real-time locations uploaded by the vehicle and thepredicted locations with the Bus Line 102 on the map, then the real-timelocations and the predicted locations may be displayed on the route onthe map in a time sequence. Thus, a smooth movement of the vehicle maybe displayed on the terminal device.

In different cases, the terminal device may display the real-timelocations or the predicted locations based on the route on the mapimplemented on the terminal device. Due to different possible errors indata uploading or positioning, the real-time locations uploaded by thevehicle or the predicted locations may not fall exactly on the route,which may require the terminal device to display such locations bymatching the locations with a preset route (e.g., projecting thelocations to the preset route). In some embodiments, the processor 210(or the terminal device) may further determine track points which areclosest to the real-time locations on the route and the predictedlocations for the vehicle from all the track points on the route at anend of a predetermined time period (i.e., the prediction generating timepoint) in 806. The terminal device may display all the determined trackpoints on the map in a time sequence.

In some embodiments, the display of the smooth movement of the vehiclealong a driving path on the map may be realized by projecting thepredicted locations and the uploaded real-time locations to the route ofthe vehicle. In some embodiments, an animation display technology may beutilized to display the smooth movement of the vehicle.

In some embodiments, the processor 210 may obtain driving data of thevehicle by performing a statistical analysis of driving data of one ormore neighboring vehicles, such as taxis or buses. The processor 210 mayuse the driving data of the one or more neighboring vehicles to estimatea predicted location of the vehicle after a predetermined time period.Merely by ways of example, the driving data of the neighboring vehiclesmay include velocities of the neighboring vehicles. In some embodiments,a predicted location for the vehicle determined based on driving data ofthe one or more neighboring vehicles can reflect the real-time locationof the vehicle more accurately, thus improving the accuracy andreliability of the smooth movement displayed on the terminal deviceeffectively.

In some embodiments, the driving data of the one or more neighboringvehicles associated with the vehicle may include durations of the one ormore neighboring vehicles to traverse one or more parts of the route. Insome embodiments, the processor 210 may determine a predicted distancethat the vehicle travels from the last uploading time point to aprediction generating time point based on the durations of the one ormore neighboring vehicles to traverse one or more parts of the route.The processor 210 may determine the predicted location of the vehicle onthe route at the prediction generating time point based on the predicteddistance and the last real-time location.

In some embodiments, the processor 210 may determine the predicteddistance from the last uploading time point to the prediction generatingtime point for the vehicle based on a prediction model. For example, theprocessor 210 may obtain a training set including historical datarelated to different parts of the route. The historical data may includehistorical durations of one or more vehicles to traverse the differentparts of the route of the vehicle. The historical data may furtherinclude, for example, a historical time point, a historical weathercondition, a historical road condition (e.g., congested or uncongested),or the like, or any combination thereof. In some embodiments, theprocessor 210 may train the prediction model using the training setaccording to a machine learning algorithm. The machine learningalgorithm may include a linear regression algorithm, a regressiondecision tree algorithm, an iteration decision tree algorithm, a randomforest algorithm, or the like, or any combination thereof. Detailsregarding the determination of the predicted locations for the vehiclemay be found elsewhere in the present disclosure, for example, FIGS.9-13 and the descriptions thereof.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 9 is a flowchart illustrating an exemplary process for displaying asmooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 900 shown in FIG. 9may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 900may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 900 may be implemented on a terminaldevice. The operations of the illustrated process 900 presented beloware intended to be illustrative. In some embodiments, the process 900may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 900 asillustrated in FIG. 9 and described below is not intended to belimiting. In an implementable method, the processor 210 may determinethe predicted location for the vehicle at an end of a predetermined timeperiod (e.g., the prediction generating time point) based on the drivingdata, a time interval between the last uploading time point and the endof a last predetermined time period, and the last real-time locationuploaded by the vehicle. In some embodiments, operations 902 and 910 maybe implemented in a similar manner as operations 802 and 806 in FIG. 8,respectively.

In 904, the processor 210 may determine a velocity of the vehicle basedon velocities of one or more neighboring vehicles.

In some embodiments, the processor 210 may obtain driving data includingthe velocities of the one or more neighboring vehicles via communicatingwith one or more service providers over a network (e.g., the network140). Merely by ways of example, the processor 210 may determine anaverage velocity based on the velocities of the one or more neighboringvehicles, and designate the average velocity as the velocity of thevehicle. In some embodiments, the processor 210 may determine a velocityof the vehicle for each predetermined time period (e.g., at the start ofthe each predetermined time period).

In 906, for each predetermined time period, the processor 210 maydetermine a predicted distance of the vehicle within a time intervalbetween the last uploading time point and the end of the eachpredetermined time period based on the velocity of the vehicle and thetime interval corresponding to the each predetermined time period.

For instance, if a bus uploads a last real-time location at 3:00:00, andthe predetermined time period is 5 seconds, a current predetermined timeperiod may end at 3:00:05, and a next predetermined time period may endat 3:00:10. The time interval from the last uploading time point to anend of the current predetermined time period (i.e., the predictiongenerating time point) may be 5 seconds (from 3:00:00 to 3:00:05). Thetime interval from the last uploading time point to an end of the nextpredetermined time period may be 10 seconds (from 3:00:00 to 3:00:10).The processor 210 may determine the predicted distance of the vehiclewithin a time interval from the last uploading time point to an end ofeach predetermined time period (i.e., the prediction generating timepoint) based on the velocity of the vehicle.

In 908, the processor 210 may determine a predicted location for thevehicle at the end of the each predetermined time period (i.e., theprediction generating time point) based on the last real-time location,the predicted distance of the vehicle within the time interval from thelast uploading time point to an end of the each predetermined timeperiod, and a route of the vehicle.

Merely by ways of example, after the processor 210 obtains the lastreal-time location uploaded by the vehicle at a last uploading timepoint, the processor 210 may obtain velocities of one or moreneighboring vehicles associated with the vehicle based on the lastreal-time location, and determine a velocity of the vehicle. For eachpredetermined time period, the processor 210 may determine a predicteddistance of the vehicle within the time interval between the lastuploading time point and the end of the each predetermined time period(i.e., the prediction generating time point) based on the velocity ofthe vehicle and the time interval between the last uploading time pointand the end of the each predetermined time period. The processor 210 maydetermine a possible location at which the vehicle may be located at aprediction generating time point (i.e., a predicted location) based onthe last real-time location uploaded by the vehicle and the predicteddistance. In some embodiments, a predetermined time period may startfrom the last uploading time point, and end at the prediction generatingtime point. In some embodiments, the end of a last predetermined timeperiod may be the start of a current predetermined time period.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 10 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 1000 shown in FIG.10 may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 1000may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 1000 may be implemented on a terminaldevice. The operations of the illustrated process 1000 presented beloware intended to be illustrative. In some embodiments, the process 1000may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1000 asillustrated in FIG. 10 and described below is not intended to belimiting. In an implementable method, the processor 210 may determinethe predicted location for the vehicle at an end of a predetermined timeperiod based on the driving data, the time length of the predeterminedtime period, and the last real-time location uploaded by the vehicle. Insome embodiments, as shown in FIG. 10, operations 1002, 1004 and 1010may be implemented in a similar manner as operations 902, 904, and 910in FIG. 9, respectively.

In 1006, the processor 210 may determine a predicted distance of thevehicle within each predetermined time period based on the velocity ofthe vehicle and a time length of the predetermined time period.

In some embodiments, the processor 210 may determine the predicteddistance of the vehicle based on a motion of the vehicle at a constantvelocity. Thus, the predicted distance may be equal to a product of thevelocity of the vehicle and a time length of the predetermined timeperiod.

In 1008, the processor 210 may determine a predicted location for thevehicle at an end of the each predetermined time period based on a lastpredicted location in a last predetermined time period, the predicteddistance of the vehicle within the each predetermined time period, and aroute of the vehicle.

Merely by ways of example, if the predetermined time period is 5seconds, and the processor 210 has determined a last predicted locationat the end of a last predetermined period at 3:00:05, the processor 210may determine a currently predicted location at 3:00:10. In someembodiments, the processor 210 may determine the currently predictedlocation at 3:00:10 based on the last predicted location at 3:00:05, thepredicted distance of the vehicle within each predetermined time period,and a route of the vehicle.

Merely by ways of example, after obtaining the last real-time locationuploaded by the vehicle at the last uploading time point, the processor210 may obtain velocities of one or more neighboring vehicles associatedwith the vehicle based on the last real-time location, and determine avelocity of the vehicle. The processor 210 may determine a predicteddistance of the vehicle within each predetermined time period based onthe velocity of the vehicle and the predetermined time period. For apredetermined time period, the processor 210 may determine a possiblelocation at which the vehicle may be located at a prediction generatingtime point (i.e., a predicted location) based on the predicted locationfor the vehicle at an end of a last predetermined time period. Theprediction generating time point may be an end of the currentpredetermined time period.

According to the embodiments shown in FIG. 9 and FIG. 10, the processor210 may determine one or more predicted locations for the vehicle, andthe terminal device may display the smooth movement of the vehicle. Thismay allow a user to visually know real-time locations and/or drivingstatus of the vehicle. The user may include a potential passenger, anadministrator that monitors and/or manages the vehicle, etc. Further, insome embodiments, since the predicted locations may change with timedeviation, there may be an error of the predicted locations. Forexample, the predicted location of the vehicle at 3:00:16 may be behindthe predicted location of the vehicle at 3:00:13. This error can beavoided by implementing the operations described in FIG. 10. In someembodiments, in the process 1000, the processor 210 may determine thepredicted location for each predetermined time period based on the lastpredicted location in a last predetermined time period, so that errorsdue to the time deviation can be avoided. Further, the map may bedivided into a plurality of grids with a certain granularity. Theprocessor 210 may obtain a location of an icon (e.g., an icon with theshape of a vehicle) in the grids of the map, and determine the predictedlocation of the icon for each predetermined time period based on thelast predicted location of the vehicle in the grids in a lastpredetermined time period. Thus, the processor 210 may ensure that thepredicted location of the icon for each predetermined time period isbehind the last predicted location in the last predetermined timeperiod.

According to the method for displaying the smooth movement of thevehicle provided by the present disclosure, when the uploading frequencyof real-time locations of a vehicle does not meet a predeterminedfrequency, the processor 210 may determine a driving status of thevehicle based on one or more neighboring vehicles. The processor 210 maydetermine a predicted location for each predetermined time period. Theterminal device may display the real-time locations and the driving pathof the vehicle on the route of the vehicle on a map. In someembodiments, the terminal device may display the smooth movement of thevehicle on the route in a form of animation, thus allowing the user tovisually know the current locations and driving status of the vehicle.This may effectively relieve the user's anxiety in a waiting process.The user may also predict an arrival time of the vehicle, and arrangehis or her own time accordingly.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 11 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 1100 shown in FIG.11 may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 1100may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 1100 may be implemented on a terminaldevice. The operations of the illustrated process 1100 presented beloware intended to be illustrative. In some embodiments, the process 1100may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1100 asillustrated in FIG. 11 and described below is not intended to belimiting. In actual scenarios, there may be some cases in which thevehicle does not move on a congested road segment or stops (e.g., near astation or before a red traffic light), and thus there is no need todetermine the predicted locations. In some embodiments, the processor210 may determine the driving status of the vehicle based on acongestion status of different parts of the route and a geographicallocation of the vehicle. In some embodiments, as shown in FIG. 11,operations 1102 and 1110 may be implemented in a similar manner asoperations 802 and 806 in FIG. 8.

In 1104, the processor 210 may determine whether the last real-timelocation is near a station on the route of the vehicle.

In 1106, if the last real-time location is near the station on the routeof the vehicle, the processor 210 may add the last real-time location tothe route, and the terminal device may display the vehicle in astationary status at an estimated location between the last real-timelocation and the station or the last real-time location on the route fora first duration on the map implemented on the terminal device.

In 1108, if the real-time location is not near the station on the routeof the vehicle, the processor 210 may determine the predicted locationfor the vehicle at a prediction generating time point based on the lastreal-time location, the last uploading time point, driving data of oneor more neighboring vehicles, and the route of the vehicle.

Merely by ways of example, after the processor 210 obtains the lastreal-time location uploaded by the vehicle at the last uploading timepoint, the processor 210 may determine whether the real-time location isnear a station on a route of the vehicle. If the real-time location isnear the station on the route of the vehicle, it may indicate that thevehicle may stop at the station, and there is no need to determine apredicted location. The terminal device may directly display the lastreal-time location on the map implemented on the terminal device anddisplay the vehicle in a stationary status. If the real-time location isnot near the station on the route of the vehicle, the processor 210 maydetermine a predicted location for the vehicle at an end of thepredetermined time period. The terminal device may display a smoothmovement of the vehicle along the route on the map from the lastreal-time location to the predicted location for the vehicle.

In some embodiments, the processor 210 may determine a distance betweenthe last real-time location and a station near the route. The processor210 may determine whether the distance is shorter than a distancethreshold. In response to the determination that the distance is shorterthan the distance threshold, the terminal device may display the vehiclein a stationary status on the map. In some embodiments, the terminaldevice may display the vehicle at the last real-time location or anestimated location between the last real-time location and the stationfor a first duration on the map. In some embodiments, the distancethreshold may be, for example, 5 meters, 10 meters, 20 meters, 25meters, etc. In some embodiments, the first duration may start from atime point when the distance between the last real-time location (or apredicted location) and the station is shorter than the distancethreshold, and end at a time point when a distance between a currentreal-time location and the station is greater than or equal to thedistance threshold. In some embodiments, the first duration may be apreset time period, such as 30 seconds, 45 seconds, etc.

According to the above embodiment, the processor 210 may determine thatthe vehicle stops at a station when the last real-time location uploadedby the vehicle currently is near a station on a route of the vehicle. Inaddition, the processor 210 may determine whether the vehicle isstationary based on one or more neighboring vehicles. For example, ifthe processor 210 determines that one or more neighboring vehicles arealso stationary, the vehicle may be in a stationary status due to acongestion or a red traffic light. If the vehicle is in a stationarystatus due to congestion or a red traffic light, the processor 210 mayadd the last real-time location to the route, and display the vehicle ina stationary status at an estimated location between the last real-timelocation and the station or the last real-time location on the route fora first duration on the map implemented on the terminal device. In thesecases, the processor 210 may not need to determine a predicted locationfor the vehicle. The terminal device may display the vehicle in astationary status on the route of the map implemented on the terminaldevice.

In addition, since the route of the vehicle is predetermined by, forexample, an administrator of the transportation information system 100,the processor 210 may also correct the real-time location uploaded bythe vehicle or the predicted location based on the route according tosome embodiments in FIG. 12. For example, the processor 210 may correctthe real-time location uploaded by the vehicle or the predicted locationbased on a predetermined bus route.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 12 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 1200 shown in FIG.12 may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 1200may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 1200 may be implemented on a terminaldevice. The operations of the illustrated process 1200 presented beloware intended to be illustrative. In some embodiments, the process 1200may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1200 asillustrated in FIG. 12 and described below is not intended to belimiting. In some embodiments, the real-time location of the vehicle maybe inaccurate. For example, a current real-time location uploaded by thevehicle may be behind a last uploaded real-time location on the routealong the driving direction of the vehicle, thus, leading to a faked Uturn. In some embodiments, operations 1202, 1206 and 1208 in FIG. 12 maybe implemented in a similar manner as operations 802, 804 and 806 inFIG. 8, respectively.

In 1204, for all the real-time locations uploaded by the vehicle, if acurrently uploaded real-time location (also referred to as “currentreal-time location”) is behind a last uploaded real-time location (alsoreferred to as “last real-time location”) on the route along the drivingdirection of the vehicle, the processor 210 may discard the currentlyuploaded real-time location.

As used herein, “ahead” and “behind” may be determined according to amoving direction of the vehicle. The moving direction of the vehicle is“ahead”, and a direction opposite to the moving direction of the vehicleis “behind”. In some embodiments, a bus on a certain Bus line may travelone-way along the route, and thus the processor 210 may correctinaccurate real-time locations based on the route. For example, theinaccurate real-time locations may be discarded. According to theembodiments described above, the processor 210 may filter the obtainedreal-time locations in advance, thus improving accuracy of the displayof the smooth movement of the vehicle on the terminal device. In someembodiments, if a currently predicted location is behind a lastpredicted location on a route along the driving direction of thevehicle, the processor 210 may discard the currently predicted location.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 13 is a flowchart illustrating an exemplary process for displayinga smooth movement of a vehicle according to some embodiments of thepresent disclosure. In some embodiments, the process 1300 shown in FIG.13 may be implemented in the transportation information system 100illustrated in FIG. 1. For example, at least a part of the process 1300may be stored in a storage medium (e.g., the nonvolatile storage 250 ofthe electronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIGS. 4-6). In someembodiments, a part of the process 1300 may be implemented on a terminaldevice. The operations of the illustrated process 1300 presented beloware intended to be illustrative. In some embodiments, the process 1300may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1300 asillustrated in FIG. 13 and described below is not intended to belimiting. In some embodiments, there may be an error in the predictedlocation of the vehicle. For example, since the predicted location isdetermined based on the predetermined time period and the driving dataof the vehicle, there may be an error between the predicted location ofthe vehicle and the real-time location of the vehicle. Merely by ways ofexample, a current real-time location uploaded by the vehicle may bebehind a last predicted location. In some embodiments, as shown in FIG.13, operations 1308 and 1310 may be implemented in a similar manner asoperations 806 and 808 in FIG. 8, respectively.

In 1302, the processor 210 may receive a current real-time locationuploaded by the vehicle. The current real-time location may refer to areal-time location uploaded at a current time point.

In 1304, if a currently displayed location is ahead of the currentreal-time location on the route along the driving direction of thevehicle, the processor 210 may freeze the currently displayed locationand display the vehicle in a stationary status until the currentreal-time location of the vehicle arrives at the predicted location. Thecurrently displayed location may refer to a location of the vehicle thatis currently displayed on a map implemented on the terminal device. Insome embodiments, the currently displayed location may be a predictedlocation. In some embodiments, the currently displayed location may be alast real-time location uploaded by the vehicle.

In 1306, if the currently displayed location is unfrozen, the processor210 may obtain the current real-time location uploaded by the vehicleand a current time point corresponding to the current real-timelocation.

For example, if a bus uploads a real-time location at 3:00:10 (i.e., alast real-time location), the processor 210 may determine a predictedlocation for the bus after 5 seconds. However, the real-time locationuploaded by the bus at 3:00:15 (i.e., a current real-time location) maybe behind the predicted location at 3:00:15, which may be because thebus does not arrive at the predicted location at 3:00:15. In someembodiments, the predicted location is displayed on the terminal device.In this case, the terminal device may display the vehicle in astationary status until the current real-time location of the vehiclearrives at the currently displayed location (e.g., the predictedlocation). For example, an icon representing the vehicle on the mapimplemented on the terminal device may be stationary until the currentreal-time location of the vehicle arrives at the predicted location.Then the terminal device may continue to display a smooth movement ofthe vehicle according to the processes described above (e.g., theprocess 900 and/or the process 1000). In this way, a zigzag movement ora back and forth movement of the vehicle on the map may be avoided.

According to the embodiment described in the process 1300, when thevehicle does not arrive at a predicted location at a certain time point,the terminal device may display the vehicle in a stationary status untilthe real-time location of the vehicle arrives at the predicted location.The terminal device may continue to display a smooth movement of thevehicle. Thus, the smooth movement of the vehicle may be realizedwithout turning back.

In some embodiments, the processor 210 may verify real-time locationsuploaded by the vehicle (e.g., a last real-time location and/or acurrent real-time location) or a predicted location determined by theprocessor 210 based on scene related information associated with adriving path of the vehicle. For example, the information acquisitiondevice 130 may obtain the scene related information from an image, avideo, an audio, etc. In some embodiments, the processor 210 mayidentify a target object from the image, the video and/or the audio, anddetermine a location of the target object on the map. The target objectmay include a shopping center, a restaurant, a city statue, a streetname and number, etc. The processor 210 may correct the real-timelocations and/or the predicted location based on the determined locationof the target object. Details regarding the correction of the locationsand/or driving paths of the vehicle will be described in connection withFIG. 21.

It should be noted that the above processes 1200 and 1300 may beperformed separately or jointly. In some embodiments, when the vehicleis turning around a corner on a road or passing through a crossroad, theprocessor 210 may determine coordinates of one or more inflection pointsof the vehicle during a turning process based on a given route. As usedherein, the inflection points may be turning points along the corner orthe crossroad of the route on the map. In some embodiments, the turningangles for the vehicle between different inflection points may bedifferent. Thus, the terminal device may display a smooth turning curveof the vehicle instead of a straight moving line. On the basis of any ofthe above embodiments, the method of displaying a smooth movement of thevehicle may further include determining one or more inflection points ofthe vehicle related to a corner or a crossroad of the route. In someembodiments, an inflection point supplementation solution may be adoptedto further smooth the turning path. In some embodiments, the processor210 may need to perform the inflection point supplementation solutionbased on a given route, and the terminal device may display thesupplemented inflection points on the given route. In this way, a moresmooth movement of the vehicle along any route (e.g., including straightline and turning) on the map implemented on the terminal device can berealized, so that the user may intuitively and accurately know thedriving status of the vehicle.

Merely by way of example, a backend server (e.g., the server 110) mayobtain real-time locations uploaded by a vehicle at intervals of one ormore predetermined time period. For those vehicles which can upload areal-time location during each predetermined time period, the terminaldevice may display one or more real-time locations of the vehicle on themap based on a route of the vehicle, so as to implement a smoothmovement. When a current real-time location uploaded at a current timepoint is behind a last real-time location uploaded at a last time point,the server 110 may correct the current real-time location. For example,the terminal device may display the vehicle in a stationary status atthe last real-time location. For a vehicle which cannot upload areal-time location during each predetermined time period, the terminaldevice may display a last real-time location at a last uploading timepoint (e.g., a start time point of a predetermined time period) and apredicted location at a prediction generating time point (e.g., an endpoint of a predetermined time period) on the map based on the route todisplay a smooth movement of the vehicle. In some embodiments, theserver 110 may determine the predicted location for the vehicle at theprediction generating time point based on the driving data of one ormore neighboring vehicles. If the vehicle makes a turn, the terminaldevice may display a smooth movement of the vehicle based on coordinatesof the real-time locations (or the predicted locations) and theinflection points of the vehicle on the route. For example, the iconrepresenting the vehicle may demonstrate a smooth turning curve along acorner or a crossroad on the route.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 14 is a flowchart illustrating an exemplary process for displayinga driving path of a vehicle according to some embodiments of the presentdisclosure. In some embodiments, the process 1400 shown in FIG. 14 maybe implemented in the transportation information system 100 illustratedin FIG. 1. For example, at least a part of the process 1400 may bestored in a storage medium (e.g., the nonvolatile storage 250 of theelectronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIG. 7). In someembodiments, a part of the process 1400 may be implemented on a terminaldevice. The operations of the illustrated process 1400 presented beloware intended to be illustrative. In some embodiments, the process 1400may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1400 asillustrated in FIG. 14 and described below is not intended to belimiting.

In 1402, the processor 210 may obtain a request for displaying a drivingpath of a vehicle from a terminal device.

In some embodiments, the processor 210 may receive a query operation todisplay a driving path of a vehicle within a historical time period.

In some embodiments, the query operation may be a request for displayingthe driving path of the vehicle in real-time. The driving path of thevehicle may be displayed on a terminal device associated with a user,such as a passenger waiting for the vehicle, an administrator, etc. Insome embodiments, the processor 210 may obtain real-time locations ofthe vehicle at a predetermined time interval and the terminal device maydisplay the driving path of the vehicle based on the real-time locationsof the vehicle. In some embodiments, the processor 210 may furtherdetermine a predicted location of the vehicle at an end of one or morepredetermined time periods based on the real-time locations of thevehicle, a velocity of the vehicle and a given route of the vehicle. Theprocessor 210 may match the predicted locations and the real-timelocations of the vehicle with the route (e.g., project the predictedlocations and the real-time locations of the vehicle to the route) andgenerate a driving path. The terminal device may display a smoothmovement of the vehicle based on the driving path on the map. Moredetails regarding displaying a driving path in real-time may be foundelsewhere, for example, in FIGS. 8-13 and the description thereof. Forillustration purposes, the process 1400 may be described as an exampleof receiving a query operation to display a driving path within ahistorical time period.

In 1404, the processor 210 may obtain location information of thevehicle within the historical time period associated with the drivingpath via communicating with a service provider over a network.

In some embodiments, the location information may be acquired by aninformation acquisition device 130 in the vehicle. The locationinformation may also be obtained by any other methods, which is notlimited in the present application. In some embodiments, the locationinformation can be acquired by a positioning device that is independentfrom the information acquisition device 130. The positioning device mayinclude any electronic device with a built-in positioning module, suchas a user's mobile phone, tablet computer, laptop computer, or the like.

The location information may include, for example, one or more locationsof the vehicle within the historical time period. In some embodiments,the location information may further include one or more time pointswhen the one or more locations of the vehicle were recorded.

In 1406, a terminal device may display the driving path of the vehicleon a map (e.g., implemented on the terminal device) based on theobtained location information.

In some embodiments, the terminal device may dynamically display agenerating process of the driving path according to an actual drivingpath generating speed of the vehicle or a displaying ratio with respectto the actual driving path generating speed. For example, an iconrepresenting a vehicle may dynamically move on the map, and form acontinuous driving path. The displaying ratio may be set and adjustedaccording to actual conditions. For example, when the displaying ratiois less than 1, the driving path is displayed in a speed slower than thedriving path generating speed. As another example, when the displayingratio is larger than 1, the driving path is displayed in a speed fasterthan the driving path generating speed. The displaying ratio can bepredefined or dynamically adjusted, for example, according to defaultsettings or adjustment by a user during an actual displaying process ofa driving path of a vehicle.

As various situations may exist during the driving process of thevehicle within the historical time period, the processor 210 may dividethe driving path of the vehicle into a plurality of segments. Theterminal device may display the divided segments with differentdisplaying properties for the plurality of segments. For example,different displaying properties may be applied to at least twoneighboring segments, so that a user (e.g., an administrator) canidentify or distinguish different segments according to the displayingproperties quickly and accurately. This may improve the viewingefficiency of the driving path of the vehicle. The displaying propertiesmay include brightness of color, hue of color, thickness of a drivingpath, or the like, or a combination thereof.

In some embodiments, the method for dividing the driving path of thevehicle into a plurality of segments may include dividing the drivingpath into a plurality of segments based on traffic conditions, timeinformation, driver information, driving data, or the like, or anycombination thereof.

In some embodiments, the processor 210 may divide the driving path intoa plurality of segments according to a distance travelled by a vehiclewithin a preset unit time. For example, the unit time may be two hours.If the processor 210 receives a request for displaying a driving path ofa vehicle within a historical time period from 8:00 to 16:00, theprocessor 210 may divide the driving path of the vehicle within thehistorical time period into four segments, each of which having adistance traveled by the vehicle in every two hours sequentially from8:00 to 16:00. In some embodiments, at least two neighboring segmentsmay have different displaying properties. In some embodiments, eachsegment may have a different displaying property, so that segmentscorresponding to different time segments (e.g., each unit time) can beeffectively distinguished. Thus, it may be convenient for theadministrator to view and/or manage different segments on the map via aterminal device.

In some embodiments, a plurality of drivers may drive the same vehiclein different time segments within a historical period. For example, thevehicle may be a shared car rented by a plurality of driversrespectively within the historical time period. As another example, abus company may have a plurality of drivers to work on a certain busline, and the drivers may shift at any stop along the bus line. Theprocessor 210 may divide the driving path into segments according todifferent drivers. For example, each of the plurality of route segmentsmay correspond to one of the drivers. For instance, the processor 210may obtain a request for displaying the driving path of the vehiclewithin a historical time period from 8:00 to 16:00. The processor 210may determine that a driver A drives the vehicle from 8:00 to 12:00 anda driver B drives the vehicle from 12:00 to 16:00. For example, thedrivers may be identified based on images or videos obtained by theinformation acquisition device 130 in the vehicle. As another example,the drivers with known identifies may drive the vehicle according to apredetermined time sequence (or a time schedule). The processor 210 maydivide the driving path into a first segment on which driver A drivesthe vehicle from 8:00 to 12:00, and a segment on which driver B drivesthe vehicle from 12:00 to 16:00. In some embodiments, differentdisplaying properties may be applied to at least two neighboringsegments. In some embodiments, each segment may have a certaindisplaying property different from other segments, so that segmentscorresponding to different drivers can be effectively distinguished.Thus, it may be convenient for the administrator to view and/or managedifferent segments on the map via a terminal device.

In some embodiments, traffic conditions may vary during a drivingprocess of a vehicle. Thus, the processor 210 may divide the drivingpath into a plurality of segments according to traffic conditions duringthe driving process of the vehicle. For example, the processor 210 mayobtain the information related to traffic conditions from a third partythat collects and stores road condition data. The third party may be aDepartment of Transportation of a country or a city. For example, theprocessor 210 may obtain a request for displaying the driving path of avehicle within a historical time period from 6:00 to 12:00. A trafficcondition during the driving process from 6:00 to 8:00 may beuncongested. A traffic condition during the driving process from 8:00 to10:00 may be congested. A traffic condition during the driving processfrom 10:00 to 12:00 may be heavily congested. The processor 210 maydivide the driving path into three segments corresponding to the trafficconditions of the three time segments. In some embodiments, words orsymbols may be used to describe the traffic conditions. For instance,the three segments may correspond to “The traffic condition from 6:00 to8:00 is uncongested”, “The traffic condition from 8:00 to 10:00 iscongested”, and “The traffic condition in 6:00 to 8:00 is heavilycongested”, respectively. In some embodiments, different displayingproperties may be applied to at least two neighboring segments. In someembodiments, each segment may have a different displaying property, sothat segments corresponding to different traffic conditions can beeffectively distinguished. Thus, it may be convenient for theadministrator to view and/or manage different segments.

In some embodiments, the processor 210 may divide the driving path intothe plurality of segments based on the driving data of the vehicle. Insome embodiments, the driving data may include a velocity of thevehicle, an accelerated velocity of the vehicle, etc. For instance, theprocessor 210 may divide the driving path based on a plurality ofvelocity ranges, such as 0-20 km/h, 20-40 km/h, 40-60 km/h, etc. A user(e.g., an administrator or a driver of the vehicle) may get to know moredetails relating to the driving status of the vehicle along the drivingpath according to the plurality of segments determined based on thedriving data. It should be noted that the driving path may also bedivided into a plurality of segments based on other types of drivingdata, which is not limited by the present disclosure.

In some embodiments, the processor 210 may obtain abnormal events of avehicle within the historical time period, and add certain labels tomark the corresponding abnormal events to locations on the driving pathwhere the abnormal events occur. For example, the abnormal events mayinclude an abrupt brake, a sudden acceleration, a sharp turn, anoverspeed behavior, or the like, or any combination thereof. Marking theabnormal events for the vehicle during the driving process on thedriving path may allow the driver, the passenger or an administrator toview the abnormal events more intuitively and conveniently.

In some embodiments, the processor 210 may obtain scene relatedinformation associated with a vehicle acquired by the informationacquisition device 130 within a historical time period. The scenerelated information may include image information related to scenesalong the driving path of the vehicle, video information related toscenes along the driving path of the vehicle, audio information relatedto scenes along the driving path of the vehicle, or the like, or acombination thereof. When the processor 210 obtains a selectionoperation of a certain time point within the historical time period, theprocessor 210 may display an image corresponding to the time point orplay a video or an audio started from the time point. Additionally oralternatively, when the processor 210 obtains a selection operation of asub-period within the historical time period (e.g., a sub-period of9:00-9:30 a.m. within a historical time period 8:00 a.m.-12:00 a.m.),the processor 210 may play a video or an audio corresponding to thesub-period. The combination of the driving path and the scene relatedinformation such as images, sounds or the like during the drivingprocess of the vehicle may allow the administrator to view the drivingpath and the scene related information more conveniently. Thus theefficiency for managing the vehicle may be improved.

In some embodiments, the processor 210 may verify the locationinformation based on the scene related information. The processor 210may identify one or more target objects on the driving path of thevehicle based on the scene related information and determine whether thelocation information of the vehicle needs to be corrected based on thetarget objects on the driving path. For example, if a location indicatedby the location information of the vehicle corresponding to a time pointis different from a location of the target object identified or inferredfrom the scene related information acquired at the same time, theprocessor 210 may determine that the location information of the vehiclecorresponding to the time point need to be corrected. If the locationinformation of the vehicle associated with the driving path needs to becorrected, the processor 210 may correct the location information of thevehicle corresponding to the time point based on the location of thetarget objects.

In some embodiments, in order to improve the accuracy of the displayeddriving path, the processor 210 may correct location information relatedto the driving path based on the acquired image information, videoinformation and/or audio information. Merely for illustration purposes,the processor 210 may identify a target object captured in the image orthe video, so as to determine geographic location information (e.g.,coordinates of geographic locations) corresponding to the target object.For instance, the processor 210 may determine the geographic locationinformation of the target subject using an image identificationtechnology. The processor 210 may correct the location informationrelated to the driving path according to the determined geographiclocation information of the target object. According to the presentdisclosure, the displaying accuracy of the driving path based on theuploaded location information can be improved. Details regarding thecorrection of the location information of the vehicle will also bedescribed in connection with FIG. 21.

In some embodiments, an image acquisition module in the informationacquisition device 130 may acquire the image information from image dataand/or video data. An audio acquisition module in the informationacquisition device 130 may acquire audio information from video dataand/or audio data. A positioning module, the image acquisition module,and the audio acquisition module may share a same clock signal of adevice to determine time information when the image data, audio dataand/or video data are recorded. In some embodiments, the processor 210may process (i.e., match, sort, group, archive, etc.) the acquireddata/information (e.g., location information, image data, video data,audio data, or the like, or any combination thereof) based on the sharedclock information.

In some embodiments, the image data, the video data, and the audio datamay also be acquired by an electronic device (e.g., a digital videorecorder (DVR) that continuously records views through a window of avehicle) that is independent from the information acquisition device130. The electronic device and the information acquisition device 130may use a same clock (e.g., a network clock), or different clocks whichare calibrated to have a same time for the electronic device and theinformation acquisition device 130 such that the location information,the image data, the video data, and the audio data acquired by differentdevices are synchronized.

In some embodiments, the location information may be acquired by apositioning device that is independent form the information acquisitiondevice 130, and the positioning device may include any electronic devicewith a built-in positioning module, such as a user's mobile phone,tablet, or the like. The positioning device and the informationacquisition device 130 may use a same clock (e.g., a network clock), ordifferent clocks which are calibrated to have a same time for theelectronic device and the information acquisition device 130 such thatthe location information, the image data, the video data, and the audiodata acquired by different devices are synchronized.

According to the present disclosure, an information acquisition device130 in a vehicle may acquire location information within a historicaltime period. A terminal device may display a driving path dynamically ona map. Thus the administrator can quickly view a driving path of thevehicle within the historical time period. The driving path and scenerelated information associated with the driving path are combined. Thescene related information may include time, images, sounds, speed, etc.,recorded during the driving process of the vehicle. Such a combinationmay reflect a relationship between the scene related information and thecontinuously changing geographical locations of the vehicle. Therefore,it may be convenient for the administrator to view and/or manage thedriving path on a map via a terminal device. Merely for illustrationpurposes, the processor 210 may obtain a request for displaying adriving path of a vehicle from a terminal device. The processor 210 mayobtain location information of the vehicle associated with the drivingpath via communicating with a service provider over a network. Theprocessor 210 may obtain scene related information associated with thedriving path of the vehicle and verify the location information based onthe scene related information; and display the driving path of thevehicle based on the verified location information on a map implementedon the terminal device.

In some embodiments, the terminal device may display a real-time drivingpath on a map implemented on the terminal device and the real-time scenerelated information associated with the driving path. For example, theterminal device may display an image, a video and/or an audio acquiredin real-time by the information acquisition device 130. The driving pathmay be displayed in the form of a smooth movement of the vehicledynamically, and the vehicle may be displayed as an icon on the drivingpath on the map.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 15 is a flowchart illustrating an exemplary process for displayinga driving path of a vehicle according to some embodiments of the presentdisclosure. In some embodiments, the process 1500 shown in FIG. 15 maybe implemented in the transportation information system 100 illustratedin FIG. 1. For example, at least a part of the process 1500 may bestored in a storage medium (e.g., the nonvolatile storage 250 of theelectronic device 200) as a form of instructions, and invoked and/orexecuted by the server 110 (e.g., the processor 210 of the electronicdevice 200, or one or more modules illustrated in FIG. 7). In someembodiments, a part of the process 1500 may be implemented on a terminaldevice. The operations of the illustrated process 1500 presented beloware intended to be illustrative. In some embodiments, the process 1500may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 1500 asillustrated in FIG. 15 and described below is not intended to belimiting. It can be seen that in an implementation of the presentapplication, data interaction among the server (e.g., the server 110),the network management system (e.g., the MIS 120), and one or moreinformation acquisition devices 130 (e.g., the information acquisitiondevice 130-1, 130-2) may be involved. The process 1500 for displaying adriving path of a vehicle will be described below in terms of datainteraction.

In 1502, the information acquisition device 130 may upload the acquireddata.

In some embodiments, the data uploaded by the information acquisitiondevice 130 may include location information, image data, video data,audio data, and/or speed information. The speed information may includeangular speed information and linear speed information. The informationacquisition device 130 may upload the acquired data in real-time or at apreset interval. In some embodiments, the information acquisition device130 may also upload a part of the acquired data in real-time, and uploadthe other part of the acquired data according to the preset interval.For example, the information acquisition device 130 may upload thelocation information in real-time, and upload the image data, the videodata, the audio data, and the speed information according to the presetinterval. It should be appreciated that the examples above are forillustration purpose, and the present disclosure is not intended to belimiting. As an example, other data uploading scheme may also be adoptedin the present disclosure.

In 1504, the server 110 may store the received data acquired by theinformation acquisition device 130.

In 1506, the MIS 120 may obtain a query operation of a driving path of avehicle within a historical time period.

In some embodiments, the query operation may be a request for displayingthe driving path of a vehicle on a terminal device within a historicaltime period or in real-time. The request may be made by a user, such asa passenger waiting for the vehicle, an administrator, etc. The MIS 120may be implemented on the terminal device, and may display the drivingpath of the vehicle and scene related information within the historicaltime period or in real-time. For illustration purposes, the process 1500may be described in a case of receiving a query operation of a drivingpath within a historical time period.

In some embodiments, when a user (e.g., an administrator) needs todisplay a driving path of a vehicle within a historical time period, theprocessor 210 may obtain the query operation of the administrator, andobtain the location information within the historical time periodacquired by the information acquisition device 130 equipped in avehicle. The MIS 120 may display the driving path on a map according tothe location information returned by the server 110.

In 1508, the MIS 120 may request the data acquired by the informationacquisition device 130 within the historical time period.

In 1510, the server 110 may return the requested data to the MIS 120.

In some embodiments, the server 110 may only return the locationinformation acquired by the information acquisition device 130 withinthe historical time period to the MIS. Alternatively, the server 110 mayalso return the location information and at least one of the image data,the video data, the audio data, or the speed information acquired by theinformation acquisition device 130 within the historical time period,which will be described in detail in the following operations.

In 1512, the MIS 120 may display a driving path of a vehicle within ahistorical time period on a map according to the acquired locationinformation.

In some embodiments, the MIS 120 may display the driving pathdynamically on the map according to an actual driving path generatingspeed of the driving path or a displaying ratio with respect to theactual driving path generating speed. For example, an icon representingthe vehicle may dynamically move on the map and form a continuousdriving path. In some embodiments, the processor 210 may divide thedriving path into a plurality of segments. Different displayingproperties (including brightness of the color, hue of the color, and/orthickness of the driving path) may be applied to at least twoneighboring segments. A process of dividing the driving path into aplurality of segments and displaying the segments on the map will bedescribed in detail below in conjunction with FIGS. 16 to 19.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 16 is a schematic diagram illustrating exemplary segments dividedbased on a unit time according to some embodiments of the presentdisclosure. In some embodiments, the processor 210 may divide thedriving path into segments according to a unit time. For example, theadministrator may need to view a driving path of a vehicle within ahistorical time period from 8:00 to 11:00, and the unit time may be setas one hour. As shown in FIG. 16, a driver may drive the vehicle from alocation A to a location B within a historical time period from astarting time point (8:00) to an ending time point (11:00). Theprocessor 210 may divide the driving path of the vehicle within thehistorical time period into three segments according to a distancetravelled by the vehicle in each hour. A “gradually changing brightness”may be used for each segment to display a generating process of thedriving path dynamically. As shown in FIG. 16, according to an actualdriving path generating speed (e.g., an actual forming speed of eachsegment) or a displaying ratio with respect to the actual driving pathgenerating speed, the route segments are separately displayed withdifferent brightness so as to display the driving path of the vehiclefrom A to B dynamically.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 17 is a schematic diagram illustrating exemplary segments dividedbased on a unit time according to some embodiments of the presentdisclosure. For a vehicle starting from a location A and arriving at alocation B, a driving path of the vehicle may be formed as shown in FIG.17 from a starting time point (8:00) to an ending time point (11:00).The driving path of the vehicle may include Segment 1, Segment 2, andSegment 3. Segment 1 corresponds to the driving path of the vehicle from8:00 to 9:00. Segment 2 corresponds to the driving path of the vehiclefrom 9:00 to 10:00. Segment 3 corresponds to the driving path of thevehicle from 10:00 to 11:00. The segments corresponding to differenttime periods (each unit time) can be effectively distinguished using the“gradually changing brightness”. Thus it may be convenient for theadministrator to view and/or manage different segments on a map via aterminal device. In some embodiments, other displaying properties mayalso be used to display each segment, such as the color hue (e.g.,“gradually changing hue”), the thickness of the driving path, etc.,which are not limited in the present disclosure.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 18 is a schematic diagram illustrating exemplary segments dividedbased on drivers according to some embodiments of the presentdisclosure. In some embodiment, the processor 210 may divide the drivingpath into a plurality of segments according to the drivers. Merely byway of example, for a vehicle that starts from a location A and arrivesat a location B, a driving path of a vehicle within a historical timeperiod from 8:00 to 11:00 may be shown in FIG. 18. The driving path ofthe vehicle may include Segment 1, Segment 2, and Segment 3. A driver xdrives the vehicle from 8:00 to 9:00 on Segment 1, a driver y drives thevehicle from 9:00 to 10:00 on Segment 2, and a driver z drives thevehicle from 10:00 to 11:00 on Segment 3. In some embodiments, a“gradually changing hue” displaying method may be used for each segmentto dynamically display a generating process of the driving path. Asshown in FIG. 18, in the driving path formed by a vehicle driving fromthe location A to the location B, Segment 1 on which a driver x drivesthe vehicle is displayed with a yellow color; Segment 2 on which adriver y drives the vehicle is displayed with an orange color; andSegment 3 on which a driver z drives the vehicle is displayed with a redcolor. The route segments corresponding to different drivers can beeffectively distinguished through the “gradually changing hue”displaying method. Thus it may be convenient for the administrator toview and/or manage different segments on the map via a terminal device.It should be appreciated that the examples above are for illustrationpurpose, and the present disclosure is not intended to be limiting. Asan example, other displaying properties may also be used to display eachsegment.

In some embodiments, in a process of dynamically displaying each segment(e.g., the process during which the vehicle travels from A to B), thedisplaying speed of each segment (actual driving path generating speedor a displaying ratio with respect to the actual driving path generatingspeed) may be associated with a distance that the vehicle passesthrough. For example, a generating process of a segment corresponding toa driver who travels a longer distance may be displayed with a higherdisplaying ratio (e.g., greater than 1) of an actual driving pathgenerating speed. A generating process of a segment corresponding to adriver who travels a shorter distance may be displayed with a lowdisplaying ratio (e.g., less than 1). In some embodiments, thedisplaying speed of each segment may be set to be associated with areas(e.g., urban area or rural area) that the vehicle passes through. Forexample, a generating process of a segment in an urban area may bedisplayed with a high displaying ratio, and a generating process of asegment in a suburban area may be displayed with a low displaying ratio.Alternatively, a generating process of a segment in an urban area may bedisplayed with a low displaying ratio, and a generating process of asegment in a suburban area may be displayed with a high displayingratio.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 19 is a schematic diagram illustrating exemplary segments dividedbased on traffic conditions according to some embodiments of the presentdisclosure. In some embodiments, the processor 210 may divide thedriving path into segments according to traffic conditions. For avehicle that starts from a location A and arrives at a location B, adriving path of a vehicle within a historical time period from 8:00 to11:00 may be shown in FIG. 19. The vehicle may have travelled three roadsegments including Road segments 1, Road segment 2, and Road segment 3within the historical time period. Road segment 1 is uncongested, Roadsegment 2 is congested, and Road segment 3 is heavily congested. Thedriving path can be divided into 3 segments (i.e., Segment 1, Segment 2,and Segment 3) according to traffic conditions corresponding to Roadsegments 1 to 3. In some embodiments, the segments corresponding to thetraffic conditions may be displayed on the map using lines havingdifferent thickness. As shown in FIG. 19, in a driving path formed by avehicle that travels from the location A to the location B dynamically,a segment with an uncongested traffic condition is displayed with a thinline. The more congested the traffic condition is, the thicker the linefor the route segment to be displayed is. The line thickness is used todisplay the congestion degree of a road segment, so that the segmentscorresponding to different traffic conditions can be effectivelydistinguished. Thus it may be convenient for the administrator to viewand/or manage different segments on the map via a terminal device. Itshould be appreciated that the examples above are for illustrationpurpose, and the present disclosure is not intended to be limiting. Asan example, other displaying properties may also be used to display eachsegment.

In a process for dynamically displaying each segment (e.g., the processin which the vehicle travels from the location A to the location B), thedisplaying speed of each segment may be an actual driving pathgenerating speed or a displaying ratio with respect to the actualdriving path generating speed. The displaying speed is not limited inthe present application.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 20 is a schematic diagram illustrating exemplary segments withlabelled abnormal events according to some embodiments of the presentdisclosure. In some embodiments, the processor 210 may determine whetherabnormal events occurred in the process for driving the vehicle based onspeed information acquired by the information acquisition device 130.For example, the abnormal events may include an abrupt brake, a suddenacceleration, a sharp turn, an overspeed behavior, or the like, or anycombination thereof. The processor 210 may add certain labels to markthe abnormal events to locations on the driving path where the abnormalevents occur. For example, as shown in FIG. 20, the vehicle had anabrupt brake at 8:35 (in Segment 1) and a sharp turn at 10:35 (inSegment 3) in the driving path. Labels “sharp brake” and “sharp turn”may be added at locations where the abnormal events occur. Thus, thedriver, the passenger, or the administrator may view the abnormal eventsassociated with the vehicle during the driving process more convenient.The operation may be simplified and the efficiency of managing thevehicle may be improved. In some embodiments, the informationacquisition device 130 may upload the acquired speed information to theserver 110. The MIS 120 may obtain the speed information from the server110, and determine whether there is an abnormal event according to thespeed information. In some embodiments, the information acquisitiondevice 130 may determine whether there is an abnormal event after thespeed information is acquired, and the determination result may beuploaded to the server 110. The MIS 120 may later obtain thedetermination result from the server 110. It should be noted that in theabove process, the server 110 may return data associated with theabnormal events (the speed information or the determination result ofthe abnormal events) together with the location information to the MIS120 when the MIS requests the location information from the server 110(the server 110 may return the location information and data associatedwith the abnormal events to the MIS 120 at the same time).Alternatively, the MIS 120 may only request the data associated with theabnormal events from the server 110, causing the server 110 to returnonly the data associated with the abnormal events to the MIS 120.

To determine abnormal events during a driving process for a vehicle, theserver 110, the MIS 120, or the information acquisition device 130 mayset thresholds for different abnormal events, such as an abrupt brake, asudden acceleration, a sharp turn, an overspeed behavior, or the like.As shown in Table 1 below, if the speed or the accelerated speed of thevehicle during the driving process exceeds a certain speed threshold oraccelerated speed threshold, the processor 210 may determine that thereis a corresponding abnormal event for the vehicle.

TABLE 1 Abnormal Event Threshold Abrupt Brake Accelerated SpeedThreshold a Sudden Acceleration Accelerated Speed Threshold b Sharp TurnAngular Speed Threshold c Over Speed Speed Threshold d

Referring back to FIG. 15, in 1514, the MIS 120 may obtain a selectionoperation of time points within the historical time period.

In 1516, the MIS 120 may display an image corresponding to the timepoint or playing a video or an audio starting from the time point.

In 1518, the MIS 120 may obtain a selection operation of a sub-periodwithin the historical time period.

In 1520, the MIS 120 may play a video or an audio corresponding to thesub-period.

In some embodiments, the server 110 may return the scene relatedinformation together with the location information to the MIS 120 whenthe MIS requests the location information from the server 110 (theserver 110 may return the location information and the scene relatedinformation to the MIS 120 at the same time). The scene relatedinformation may be determined based on data acquired by the informationacquisition device 130, including image data, video data, video data, orthe like, or any combination thereof. Alternatively, the MIS 120 mayrequest the scene related information alone from the server 110, so asto cause the server 110 to return the scene related information to theMIS 120. The information exchange among the server 110, the MIS 120, andthe information acquisition device 130 is not limited in the presentdisclosure. The combination of the driving path and the scene relatedinformation during the driving process of the vehicle (e.g., the imagesand/or sounds) may allow the administrator to obtain informationrelevant to the vehicle more quickly and more conveniently. Thus theefficiency for managing the vehicle may be improved.

The processor 210 may correct/verify the driving path based on theacquired image data, audio data, or video data. For example, theprocessor 210 may identify a target object in the image data or thevideo data so as to determine a geographic location informationcorresponding to the target object. In some embodiments, the geographiclocation information of the target subject may be determined using animage identification technology. The processor 210 may correct/verifythe location information and/or a driving path of a vehicle according tothe determined geographic location information. Thus the displayingaccuracy of the driving path of the vehicle can be improved.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 21 is a schematic diagram illustrating an exemplary correction of adriving path of a vehicle according to some embodiments of the presentdisclosure. As shown in FIG. 21, the MIS 120 may determine an “originalpath” according to the acquired location information. The original pathmay refer to a driving path determined based on the acquired locationinformation of the vehicle. For example, in the original path, thevehicle may drive on Street 1. The MIS 120 may identify a “CitizenCenter” in the acquired image data, audio data, and/or video data, anddetermine that the “Citizen Center” is located on one side of Street 2.Thus the MIS 120 may correct a part of the “original path” i.e., onStreet 1 into a corrected route, i.e., on Street 2. Thus a correctdriving path (e.g., a driving path in dark color from the location A tothe location B of the vehicle in FIG. 21) may be obtained.

In some embodiments, a variety of modules of the information acquisitiondevice 130 may acquire the location information, the image data, thevideo data, the audio data, the speed data, or the like, respectively.These modules may use a same clock (e.g., a network clock), or differentclocks which are calibrated to have a same time for the electronicdevice and the information acquisition device 130 such that the locationinformation, the image data, the video data, the audio data, and/or thespeed data acquired by different devices are synchronized. Thus the MISmay display an image, or play a video or an audio corresponding to aselected time point or sub-period. The MIS may also correct the locationinformation according to the image data or the video data.

According to the above embodiments of the present disclosure, the MIS120 may obtain location information acquired within a historical timeperiod by the information acquisition device 130 equipped in a vehicle.The MIS 120 may display the driving path of the vehicle in a form of adynamically forming driving path, so that the administrator can quicklyview a driving path of the vehicle within the historical time period. Insome embodiments, the MIS 120 may display the driving path and the scenerelated information acquired during the driving process of the vehiclemay, which may allow the administrator to obtain information relevant tothe vehicle more quickly and more conveniently. The scene relatedinformation may include an image, a video, an audio, or the like, or acombination thereof. Thus the efficiency for managing the vehicle may beimproved.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skill in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure, and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “unit,” “module,” or “system.” Furthermore, aspects ofthe present disclosure may take the form of a computer program productembodied in one or more computer readable media having computer readableprogram code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C #, VB.NET, Python or the like, conventional procedural programming languages,such as the “C” programming language, Visual Basic, Fortran 2003, Perl,COBOL 2002, PHP, ABAP, dynamic programming languages such as Python,Ruby and Groovy, or other programming languages. The program code mayexecute entirely on the user's computer, partly on the user's computer,as a stand-alone software package, partly on the user's computer andpartly on a remote computer or entirely on the remote computer orserver. In the latter scenario, the remote computer may be connected tothe user's computer through any type of network, including a local areanetwork (LAN) or a wide area network (WAN), or the connection may bemade to an external computer (for example, through the Internet using anInternet Service Provider) or in a cloud computing environment oroffered as a service such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose, and that the appendedclaims are not limited to the disclosed embodiments, but, on thecontrary, are intended to cover modifications and equivalentarrangements that are within the spirit and scope of the disclosedembodiments. For example, although the implementation of variouscomponents described above may be embodied in a hardware device, it mayalso be implemented as a software only solution, e.g., an installationon an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various embodiments. This method ofdisclosure, however, is not to be interpreted as reflecting an intentionthat the claimed subject matter requires more features than areexpressly recited in each claim. Rather, claimed subject matter may liein less than all features of a single foregoing disclosed embodiment.

We claim:
 1. A method implemented on a computing device having at leastone processor, at least one computer-readable storage medium, and acommunication platform connected to a network for displaying a smoothmovement of a vehicle on a map, the method comprising: obtaining a routeof a vehicle via communicating with a service provider over a network;obtaining a last real-time location of the vehicle on the route and alast uploading time point corresponding to the last real-time location;obtaining driving data of one or more neighboring vehicles associatedwith the vehicle via communicating with the service provider over thenetwork, wherein the driving data of the one or more neighboringvehicles associated with the vehicle includes durations of the one ormore neighboring vehicles to traverse one or more parts of the route;determining a predicted location of the vehicle on the route at aprediction generating time point based on the last real-time location,the last uploading time point, and the driving data of one or moreneighboring vehicles associated with the vehicle; and displaying asmooth movement of the vehicle from the last real-time location to thepredicted location on a map implemented on a terminal device.
 2. Themethod of claim 1, wherein the driving data of the one or moreneighboring vehicles associated with the vehicle includes velocities ofthe one or more neighboring vehicles.
 3. The method of claim 2, whereindetermining the predicted location of the vehicle on the route at theprediction generating time point includes: determining a velocity of thevehicle based on velocities of the one or more neighboring vehiclesassociated with the vehicle; determining a predicted distance that thevehicle travels from the last uploading time point to the predictiongenerating time point based on the velocity; and determining thepredicted location of the vehicle on the route at the predictiongenerating time point based on the predicted distance and the lastreal-time location.
 4. The method of claim 1, wherein determining thepredicted location of the vehicle on the route at the predictiongenerating time point includes: determining a predicted distance thatthe vehicle traverses from the last uploading time point to theprediction generating time point based on the durations of the one ormore neighboring vehicles to traverse one or more parts of the route;and determining the predicted location of the vehicle on the route atthe prediction generating time point based on the predicted distance andthe last real-time location.
 5. The method of claim 1, furtherincluding: determining a distance between the last real-time locationand a station near the route; determining whether the distance issmaller than a threshold; and in response to the determination that thedistance is smaller than the threshold, displaying the vehicle in astationary status at a predicted location between the last real-timelocation and the station for a first duration on the map implemented onthe terminal device.
 6. The method of claim 1, further including:obtaining a current real-time location of the vehicle; determiningwhether the predicted location at the prediction generating time pointis ahead of the current real-time location of the vehicle; and inresponse to the determination that the predicted location at theprediction generating time point is ahead of the current real-timelocation of the vehicle, displaying the vehicle in a stationary statusat the predicted location on the map implemented on the terminal deviceuntil the current real-time location of the vehicle arrives at thepredicted location.
 7. A system for displaying a smooth movement of avehicle on a map, comprising: at least one storage medium storing a setof instructions; at least one communication platform connected to anetwork; and at least one processor configured to communicate with theat least one storage medium or the at least one communication platform,wherein when executing the set of instructions, the at least oneprocessor is directed to cause the system to: obtain a route of avehicle via communicating with a service provider over a network; obtaina last real-time location of the vehicle on the route and a lastuploading time point corresponding to the last real-time location;obtain driving data of one or more neighboring vehicles associated withthe vehicle via communicating with the service provider over thenetwork, wherein the driving data of the one or more neighboringvehicles associated with the vehicle includes durations of the one ormore neighboring vehicles to traverse one or more parts of the route;determine a predicted location of the vehicle on the route at aprediction generating time point based on the last real-time location,the last uploading time point, and the driving data of one or moreneighboring vehicles associated with the vehicle; and display a smoothmovement of the vehicle from the last real-time location to thepredicted location on a map implemented on a terminal device.
 8. Thesystem of claim 7, wherein the driving data of the one or moreneighboring vehicles associated with the vehicle includes velocities ofthe one or more neighboring vehicles.
 9. The system of claim 8, whereinto determine the predicted location of the vehicle on the route at theprediction generating time point, the at least one processor is furtherdirected to cause the system to: determine a velocity of the vehiclebased on velocities of the one or more neighboring vehicles associatedwith the vehicle; determine a predicted distance that the vehicletravels from the last uploading time point to the prediction generatingtime point based on the velocity; and determine the predicted locationof the vehicle on the route at the prediction generating time pointbased on the predicted distance and the last real-time location.
 10. Thesystem of claim 7, wherein to determine the predicted location of thevehicle on the route at the prediction generating time point, the atleast one processor is further directed to cause the system to:determine a predicted distance that the vehicle traverses from the lastuploading time point to the prediction generating time point based onthe durations of the one or more neighboring vehicles to traverse one ormore parts of the route; and determine the predicted location of thevehicle on the route at the prediction generating time point based onthe predicted distance and the last real-time location.
 11. The systemof claim 7, wherein the at least one processor is further directed tocause the system to: determine a distance between the last real-timelocation and a station near the route; determine whether the distance issmaller than a threshold; and in response to the determination that thedistance is smaller than the threshold, display the vehicle in astationary status at a predicted location between the last real-timelocation and the station for a first duration on the map implemented onthe terminal device.
 12. The system of claim 7, wherein the at least oneprocessor is further directed to cause the system to: obtain a currentreal-time location of the vehicle; determine whether the predictedlocation at the prediction generating time point is ahead of the currentreal-time location of the vehicle; and in response to the determinationthat the predicted location at the prediction generating time point isahead of the current real-time location of the vehicle, display thevehicle in a stationary status at the predicted location on the mapimplemented on the terminal device until the current real-time locationof the vehicle arrives at the predicted location.
 13. A non-transitorycomputer readable medium, comprising a set of instructions fordisplaying a smooth movement of a vehicle on a map, wherein whenexecuted by at least one processor, the set of instructions directs theat least one processor to effectuate a method, the method comprising:obtaining a route of a vehicle via communicating with a service providerover a network; obtaining a last real-time location of the vehicle onthe route and a last uploading time point corresponding to the lastreal-time location; obtaining driving data of one or more neighboringvehicles associated with the vehicle via communicating with the serviceprovider over the network, wherein the driving data of the one or moreneighboring vehicles associated with the vehicle includes durations ofthe one or more neighboring vehicles to traverse one or more parts ofthe route; determining a predicted location of the vehicle on the routeat a prediction generating time point based on the last real-timelocation, the last uploading time point, and the driving data of one ormore neighboring vehicles associated with the vehicle; and displaying asmooth movement of the vehicle from the last real-time location to thepredicted location on a map implemented on a terminal device.
 14. Thenon-transitory computer readable medium of claim 13, wherein the drivingdata of the one or more neighboring vehicles associated with the vehicleincludes velocities of the one or more neighboring vehicles.
 15. Thenon-transitory computer readable medium of claim 14, wherein determiningthe predicted location of the vehicle on the route at the predictiongenerating time point includes: determining a velocity of the vehiclebased on velocities of the one or more neighboring vehicles associatedwith the vehicle; determining a predicted distance that the vehicletravels from the last uploading time point to the prediction generatingtime point based on the velocity; and determining the predicted locationof the vehicle on the route at the prediction generating time pointbased on the predicted distance and the last real-time location.
 16. Thenon-transitory computer readable medium of claim 13, wherein determiningthe predicted location of the vehicle on the route at the predictiongenerating time point includes: determining a predicted distance thatthe vehicle traverses from the last uploading time point to theprediction generating time point based on the durations of the one ormore neighboring vehicles to traverse one or more parts of the route;and determining the predicted location of the vehicle on the route atthe prediction generating time point based on the predicted distance andthe last real-time location.
 17. The non-transitory computer readablemedium of claim 13, the method further including: determining a distancebetween the last real-time location and a station near the route;determining whether the distance is smaller than a threshold; and inresponse to the determination that the distance is smaller than thethreshold, displaying the vehicle in a stationary status at a predictedlocation between the last real-time location and the station for a firstduration on the map implemented on the terminal device.